7 Jun 2013 - published elsewhere or extracted in whole, or in part, for a ..... Trumpf laser .... prices, maintenance budget, and cost of spares, asset values, ...
DEVELOPING AND IMPLEMENTING AN OPTIMAL MAINTENANCE STRATEGY TO INCREASE THE RELIABILITY AND AVAILABILITY OF THE TOW BAR PAINT LINE AT TRIMAS CORPORATION
A dissertation submitted by
JOEL NYONI
In partial fulfilment of the requirements of
MASTER OF MAINTENANCE MANAGEMENT
School of Engineering and Technology Higher Education Division Central Queensland University June 2013
DEVELOPING AND IMPLEMENTING AN OPTIMAL MAINTENANCE STRATEGY TO INCREASE THE RELIABILITY AND AVAILABILITY OF THE TOW BAR PAINT LINE AT TRIMAS CORPORATION
JOEL NYONI
Student number: S0171343
MASTER OF MAINTENANCE MANAGEMENT
Academic supervisor: Dr Subhash Sharma
Industry supervisor: Sinu Pillai
School of Engineering and Technology Higher Education Division Central Queensland University June 2013
ABSTRACT Trimas Corporation’s Tow Bar Paint Line has been a critical investment. The organisation commissioned this plant in Melbourne in December 2011 after spending about $5million. The Paint line is a key asset but has presented itself with major reliability and availability problems. This plant or asset has been producing products with inconsistent quality rates and at the same time breaking down more often than it should be producing. The asset’s reliability and availability rates are below required benchmarks and have caused significant financial losses to the company. As a result, this has brought mixed morale to maintenance, production, contractors and also top management. These problems of lack of reliability and availability have been under investigation prompting the objective of this thesis. Information has been acquired from production operators’ log sheets, maintenance job cards and asset history. Additional data was collected from the original equipment manufacturers, Luxford Australia and Garnic Technologies and also Laser Electrical who are the main contractors. The use of problem solving techniques like the Fault tree, Ishikawa method, Failure mode and effect analysis (FMECA) and Root cause analysis (RCA) were used to find the root cause of problems. The questions asked more often were, could it be the lack of application of leading edge design, maintenance policies and systems, procedures, methods and technologies that has caused poor reliability of this asset? In this research, a thorough investigation has been carried out and all the above aspects have been looked into. These include skills and knowledge of production and maintenance personnel including contractor harmony and performance. The investigations concluded that management policy on systems reliability, maintenance strategy; organisational structure and lack of continuous improvement drive were the main causes of poor reliability and these need special attention. On completion of this research recommendations to improve the efficiency and effectiveness of the Paint Line have been made. The recommendations include changes in the organisational structure, maintenance strategies and troubleshooting points on the production process. A method called PIE-C and Asset Reliability Stream have been recommended to set up an efficient and effective maintenance
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organisation. The Asset Reliability Stream would be used to guide and implement the necessary processes and structures to achieve reliability excellence. The PIE-C would be used to ensure each process and stage of the Asset Reliability stream is properly implemented, evaluated and improved. Finally the research suggests the Paint Line plant should undergo periodic evaluation and continuous improvement until optimal reliability excellence is achieved.
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ACKNOWLEDGEMENT I have taken great time and effort in this thesis and I would like to thank some people who took their time to support me. I would like to give special gratitude to my academic supervisor Dr. Subhash Sharma, Head of Discipline, (Maintenance management) at CQUniversity. He provided assistance and direction during long hours of discussions at the Melbourne campus and on the phone. I would also like to thank my industrial supervisor Sinu Pillai, Senior Quality Engineer and Christian Cortina, the Maintenance manager at Trimas Corporation in Melbourne for their valued direction and encouragement. I am highly indebted to Trimas Production staff for wilfully providing me with production and operations information. I also give thanks to the Trimas maintenance department team for their cooperation, and Rob Tedesco (Maintenance supervisor) who afforded me time to acquire maintenance information for this project. My thanks and honour goes to my wife Vimbai and family for their unwavering support during this project.
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DECLARATION OF ORIGINALITY
Statement of Authorship Except where reference is made in text, this thesis contains no information published elsewhere or extracted in whole, or in part, for a submission by me for another degree.
No other persons’ work has been used without due acknowledgement in the main text of the thesis.
This thesis not been submitted by me in any other degree in any other university
Signed……………Joel Nyoni
Date……….. 7th June 2013
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TABLE OF CONTENTS Abstract………………………………………………………………....i Acknowledgement……………………………………………………...iii Statement of Original authorship……………………………………..iv Table of contents…………………………………………………….….v List of figures…………………………………………………………..vii List of tables……………………………………………………………ix Chapter 1 1.1ntroduction……………………………………………………….....1 1.1 Background of Trimas Corporation…………………………………1 Chapter 2 Problem formulation 2.1 Paint Line Operating Process………………………………………..5 2.1.1 The Conveyor system………………………………….…………..……5 2.1.2 The Airless shot blaster……………………………….………………..8 2.1.3 The E-coat and ancillary system…………………………………..9 2.2. Problem analysis…………………………………………………...10 2.3 Research Methodology……………………..………………………13 2.3.1 Survey and data collection…………………………………………....14 2.3.2 Data analysis…………………………………………………………....15 2.3.3 Observations………………………………………………………….....15 2.3.4 Recommendations………………………………………………....15 Chapter 3 Literature Review 3.1 Introduction……………………………………………………….....16 3.2 Objectives of the Paint Line study…………………….…………….16 3.3 The maintenance organisation……………………………………….17 3.4 Early studies of maintenance practices and concepts………..………18 3.5 The maintenance operating concept…………………………………18 3.6.1 Reliability…………………………………………………….……………20 3.6.2 Availability…………………………………………………………22 3.7 Asset assessment and investigative tools…………………………....23 3.7.1 Root Cause Analysis……………………………………………..………23 3.7.2 Failure mode and effect criticality analysis………………..…………24 3.7.3 Fault Tree Analysis……………………………………….…….………..26 3.7.4 Cause and effect analysis (Fishikawa method)…….…….…………..27
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3.7.5. Condition Monitoring………………………………………………29 3.7.6. Mathematical probability models……………………………………....30 3.7.7 Conclusion of Problem solving tools……………………...…………….36 3.8 Reliability optimisation policies……………………………….………36 3.9 The risk factor in maintenance…………………………………..…….38 3.10 Maintenance frameworks…………………………………………….38 3.10.1 Introduction……………………………………………….……………….38 3.10.2 Total productive maintenance………………………….….…………….40 3.10.3 Business centred maintenance……………………………………………41 3.10.4. Reliability centred maintenance…………………………………………43 3.10.5 Predictive maintenance……………………………………………………44 3.10.6. Preventive maintenance……………………………………………….…45 3.11 Conclusion of the Literature review……………………………..…….47 3.12 Evaluation of current state and gaps……………………………………47 Chapter 4 Solution to the problem 4.1 Introduction……………………………………………………………..49 4.2 Human effect in attaining reliability…………………………………....49 4.2.1 The effect of various human elements in the organisation………….....50 4.2.2 Observations………………………………………………………….………52 4.3 Mean time between failures (MTBF)………………………….………..53 4.4 Mean time to repair (MTTR)……………………………...…………….54 4.5 Downtime………………………………………………….……………55 4.6 Overall equipment efficiency……………………………….…………..56 4.7 Data interpretation……………………………………………………….57 4.8 The Asset Reliability stream……………………………………………..58 4.9 Equipment criticality ranking…………………………………………….60 4.9.1 Identification of critical assets………………………………………………60 4.9.2 Criticality scoring results…………………………………………………….61 4.9.3 Data interpretation and impact assessment……………….……………….63 Chapter 5 Recommendations 5.1 Introduction…………………………………………………..………….65 5.2 Changes to the organisational structure………………………….………65 5.3 Re-designs and development to the Paint Line……………………..……69 5.4 Implementation of the reliability care plan of the Paint Line…………….71 5.4.1 Introduction……………………………………………………………………71 5.4.2 Application of problem solving methodologies………………..………….72
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5.4.3 Improvements on Total productive maintenance……………..…………73 5.4.4 Daily inspections and start-ups……………………………………………74 5.4.5 Predictive maintenance/ Condition monitoring………………………….74 5.4.6 Operate to fail (OTF)……………………………………………….....76 5.4.6.1 Operate to fail application areas……………………………….……….76 5.4.7 Shutdown/ Turnaround maintenance………………………………….76 5.4.7.1 Turnaround scope……………………………………………………….….77 5.5 The Computerized maintenance management system (CMMS)……...…78 5.6 Spares management…………………………………………..………….79 5.6.1 Inventory policy………………………………………………….……………80 5.6.2 Rotables………………………………………………………………………...80 5.6.3 Use CMMS in spares management……………………………………..82 5.7 The E-coat process: Troubleshooting recommendations………………….82 5.7.1 The E-coat troubleshooting process…………………………….…………..83 5.7.2 The E-coat preventive measures……………………………..………………83 5.7.3 Parameter effects on quality…………………………………….……………85 5.7.4 Common electroplating defects caused by equipment failure……………85 Chapter 6 Conclusion Conclusion……………………………………………………………………87 Areas of future research……………………………………………………...88 References……………………………………………………………………90 Appendices…………………………………………………………………...93
List of Figures Figure 1 Trimas Corporation’s Strategic Aspirations and Mission…....2 Figure 2 Airless shot blaster and Pre-treatment plant…………………2 Figure 3 Trimas Plant layout………………………………………….6 Figure 4 Paint Line Main equipment availability chart…………..……7 Figure 5 Overhead conveyor……………………………………….….8 Figure 6 Airless shot blaster………………………………………..….9
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Figure 7 Wash booth and e-coat pump………………………………..10 Figure 8 Methodology plan……….......................................…………13 Figure 9 Maintenance organisation: internal output centre…………....17 Figure 10 Flow chart of the maintenance system……………………...20 Figure 11 Reliability Engineering strategy for the Paint Line...………..21 Figure 12 Maintainability diagram of the e-coat pump………..………25 Figure 13 Fault tree diagram of Paint Line chain………..…………….27 Figure 14 Fishikawa/Cause and effect diagram………….……………28 Figure 15 pdf curve…………………………………………………....31 Figure 16 Confidence rates data sets of the conveyor…………………33 Figure 17 Simplified Bayesian network of the conveyor chain….…….34 Figure 18 Markov random field model………………………………....35 Figure 19 Maintenance task/ method determination…………………....39 Figure 20 Business centred maintenance (BCM) thought process……..42 Figure 21 Degradation curve or p-f curve………………………………44 Figure 22 Bath tub curve of the Paint Line……………………..………46 Figure 23 Asset reliability stream……………………………….………58 Figure 24 PIE-C Method………………………………………………..59 Figure 25 Current organisational structure…………………….……….66 Figure 26 Proposed organisational structure………………...………….67 Figure 27 Brushes installed for cleaning power chains…………...…….69 Figure 28 Frameworks to strengthen Paint Line structure…….….……..70 Figure 29 E-coat pump and rinse system problems…………………......72
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Figure 30 Conveyor chain trolleys and bearings to be reconditioning…......81 Figure 31 Critical conveyor parts held as spares………………………..….82
List of tables Table 1.Scoring rating for humans in the organisation……………………50 Table 2.The tabular result for each human element in the organisation…...51 Table 3.Equipment criticality ranking weightings…………………….…..60 Table 4.The Human consequence table……………………………………60 Table 5.Environmental effects……………………………………......……61 Table 6.Equipement criticality ranking of the Paint Line……………….....62 Table 7.Application of problem solving methodologies………...…………73 Table 8.Equipement to monitored by predictive technology……………….75 Table 9.Fast moving spares…………………………………………………80 Table 10.Slow moving spares……………………………………………….80 Table 11.Allocation of rotables workload…………………………….……..81 Table 12.How equipment problems cause product defects……….…......….86 List of Appendices Appendix A….Paint Line Availability log sheet A………………...…93 Appendix B…..Paint Line Availability Log sheet B………………….94 Appendix C…..Paint Line Availability Log sheet C………………….95 Appendix D…..E- Coat and Pre-treatment performance log sheet……96 Appendix E…...Garnic Technologies (OEM) failures log sheet………97
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CHAPTER 1 Introduction
1.1 Background: Trimas Corporation Trimas Corporation’s Cequent Asia Pacific is a manufacturer and distributor of motor car tow bars, cargo barriers, side steps, bull bars and roof racks. The manufacturing facility is located in the Keysborough Estate in the south eastern metropolitan area of Melbourne. Trimas Corporation is the parent company based in the United States, in Bloomfield Hills, Michigan and the organisation operates in 15 countries with about 4000 employees working in its different divisions namely Aerospace, Defence, Packaging, Engineered Products, Energy, Cequent North America and Cequent Asia Pacific. (Trimas Corp, 2012). Cequent Asia Pacific has a net sales contribution of $26.5Million, thus it plays a vital role in forming the organisation strategies of growth and profitability. In this respect the Tow Bar Paint Line has been found to be one of the most critical assets that contribute to overall productivity in the organisation. The current rate of downtime is 40%, and this has been retrogressive to the goal of the organisation. This has to be reduced. Figure 1 shows the “Strategic Aspirations and Mission” of Trimas Corp. It articulates the vision of the organisation and how it is determined to increase production and strategize itself for the future. Through the Strategic Aspiration and Mission, Trimas Corporation aims to: Achieve overall increase of sales revenue by at least 15% by the year 2013. Invest in current and future growth to expand and satisfy customers through acquisition of new equipment like the new Melbourne Tow bar Paint Line. Focus on lean activities and low cost production that will bring productivity savings to 3-5%. Continue to reduce fixed costs and simplify business so as to improve on customer supply lead time, service and overall competitiveness. Maximize shareholder value and also generate single digit top line growth. Finally making Trimas a great workplace (Trimas corp., Quarterly, 2012).
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Growth PRIORITY
Asset Efficiency
Trimas operating policy
REWARD
FOCUS
Productivity
ACCOUNTABILITY
People development
Figure 1 The Strategic Aspirations and Mission of Trimas Corporation. (Trimas Quarterly, Sept 2011). In view of the above vision, management at the Melbourne facility have a huge task to undertake in order to transmit the above mission and ambitions of the directors and shareholders of the organisation into reality.
(a)The Airless shot blaster (b)Entrance to the Pre-treatment (Trimas Corp) section of the Paint Line (Trimas Figure 2 a) Airless shot blaster, b) Pre-treatment section of the Paint Line. (Trimas Corp) Corp. 2013)
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To fulfil the business expansion and operational efficiency, Trimas brought its two facilities, the Waterview Close plant and Abbots Road plant under one facility known as the Keysborough facility, located in the state of Victoria, Australia. The consolidation process also came with acquisition of new assets namely new Flatbed lasers, Hydraulic presses, Welding equipment, Compressors and also a new Tow bar Paint Line. It is the Tow bar Paint Line shown partly in Figure 2, which will be the subject of this thesis. Its function and problems will be explained in the following Chapter 2. This thesis is centred on the need to improve optimally, the reliability and availability of the Paint Line. Thus in Chapter 3, a Literature review was undertaken where various methods used for identifying causes of low Availability by other practicing engineers were discussed. Methodologies like RCA, Fishbone, FMECA and probability based reliability methods were evaluated confirming the importance of pin pointing the root cause of equipment problems. The Literature review also shows that some organisations use different methodologies like the Plan –Do check cycle and maintenance strategies like basic preventive maintenance to overcome equipment problems. Some organisations have resorted to have solved this type of problems by instituting complete overhauls or turnaround of the equipment. In cases where problems are mitigated by design factors most equipment is improved through modifications and product simulation after identifying problem areas. In this case the Asset Reliability Stream has been used to map out the process of ensuring that all stages and systems are in place to attain high reliability of the plant. Furthermore human resources also play a major role in improving the performance of the maintenance organisation thus factors that contribute to plant reliability were analysed. In order to have an efficient and effective work force some strategies and conditions like recruitment, training and staff motivation were reviewed. In Chapter 4, a comprehensive solution to the problem was developed to achieve a higher availability rate of the Paint Line. An asset criticality hierarchy was drawn for the Paint Line followed by recommendations of best identified maintenance methodologies for critical equipment.
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Based on the findings and interpretation of the investigating data, ways to improve plant reliability and availability were presented in Chapter 5. Besides that some specific detail was given for troubleshooting problems on production equipment that affect product quality because of poor equipment health and non-adherence to process parameters. Capping it all, a new organisational structure that would suit the operations and maintenance of the Paint Line was drafted. The cost of downtime, plant performance and maintenance organisation effectiveness were all compiled to justify the recommendations. It is expected if the outcome of this analysis is implemented the Reliability and Availability rate of the Paint Line would improve significantly.
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CHAPTER 2 PROBLEM FORMULATION 2.1 Paint Line operating process In this thesis the term “product” means tow bars, bull bars, cargo barriers or other metal parts manufactured at Trimas Corporation. The Paint Line is used to process and convey product from welding or production bays in the factory. The product passes through an Airless Shot Blaster where it is descaled and afterwards cleaned by high pressure air jets at the exit. The product is then conveyed through the PreWash treatment chamber and then through the chemical dosing chamber. After that it is rinsed and then conveyed through the E-coat paint dip tank. The product is then passed through the Drip chamber and then through a Drying Oven where the paint dries up. After that the product will then pass through the Powder Coat spray booth where it is powder coated and is dried as it passes through the curing oven. It is then cooled in the package lanes ready for dispatch to customers. The manufacturing process is shown below in Figure 3. The problems of the Paint Line will be explained according to the main sections which are as follows: 1. Conveyor system. 2. Airless Shot Blaster. 3. E-coat and its ancillary equipment. 2.1.1 The Conveyor system The conveyor structure is made up of a power chain rail track braced on top of a power free rail track. Load or product bars are fitted with one end on the trailer trolley and the other end on a leading accumulating trolley. This assembly travels on the free trolley rail track and is driven by the power chain. This power chain is driven by meshing variable speed drive chains. The conveyor has pneumatic chain tensioners and sensors for controlling the chain tension and location of load bars on the conveyor system. The conveyor operation is controlled by the FAT control system which shows the whole Paint Line systems, conveyor speed, and position of gates, mergers, temperature of baking ovens and other process parameters.
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Trumpf laser tube cutter
Hydraulic bending machines
Parts, subassemblies inspection
Flatbed laser cutting section
Admin offices
Bulk metal saws
Compressors
Robotic welding cells Quality control
FINAL ASSEMBLY WELD BAYS
Trades workshop
Dispatch & warehouse offices
Quality control Finishing and packing bays
FAT controller
Airless shot blaster
Bake oven
Powder coat booth
Curing oven
Pre-wash treatment
E-coat dip tank
Permeate rinse
Figure 3 Trimas Plant layout (Source: Trimas Corp)
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70 Availability %
60
50
40 Conveyor chain E-coat system 30
Shot blaster
20
10
0 Week 1
Week 2
Week 3
Week 4
Figure 4 Paint Line main Availability chart for August 2012. According to the feedback information from the Availability Log sheets shown in Appendices A, B and C, and the failure chart Figure 4 the conveyor system had the following main problems that lowered it availability and reliability rating: Chain drive unit motor was continuously tripping due to over torque. This resulted in lost time, taking between 5minutes to an hour to fix. The power chain snaps, stuffs or jams on entrance or exit of chain drive unit. This problem causes a major share of down time. This takes up to 3-6 hours before the line is operational again.
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Figure 5 Overhead conveyor. (Source: Trimas Corp) The product or tow bars drop in the path or are hooked on the sides of ovens or dip tank. This problem could take up to an hour if it is not discovered early, causing lost time. Stopper, merger and diverter units had recurring failures. These problems continued to dog the Paint line causing load bars from merging rails to collide and damage the rails. Failure to de-dog. When this happens the chain is stretched and the drive motor trips. It had been difficult to ascertain the cause of motor over torque although a number of issues that directly caused this were found out and some are still being investigated. 2.1.2 The Airless shot blaster This is used for descaling tow bars or product before washing in the pre- wash chambers. Descaling is done by the use of shooting steel shot to tow bar surface using high speed centrifugal impellers. The shot blaster problems were as follows: Blocked chutes. The chutes were often blocked by swarf and other foreign material thus cutting supply to centrifugal impellers causing poor descaling. Estimated down time ranged from 30 minutes to 2 hours.
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Figure 6 Airless shot blaster and feed conveyor. (Source: Trimas Corp) Motor overload or failure. This failure is caused by too much shot to the impellers. This caused another 30 minutes to 2 hours lost time in clearing the blockage. Shot bucket elevator jamming and causing motor over torque and stuffing shot on the cross and longitudinal screw conveyors. This is classified a major breakdown and takes 4-6 hour to clear up. Quality loss. The wearing out of the vestibule seals caused not only low quality descaling but ingress of shot into the conveyor chain track system leading to down time of 4hrs to 2 days. 2.1.3 E-coat and ancillary equipment The E-coat comprises of the pre-wash chamber, zinc phosphate tanks and circulation pumps. The tow bars undergo washing by chemical water and are then washed in deionized water before electrocoating in the dip tank. After electroplating the tow bars pass through the permeate rinse then through the curing oven. From the curing oven the bars pass through the powder coat booth and then into the baking oven. The bars are then packed in the finishing bay.
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a)
b)
Figures 7 (a) wash booth (b) e-coat tank with pumps (Source: Trimas Corp)
The problems in this area are as follows; Failure of circulation pumps, leaking seals, faulty tank floats and spray nozzles. All these cause ineffective cleaning; rinsing and ultimately poor electrocoating thus producing poorly finished products. Power failure on E-coat rectifiers. This takes place in the dip tank and is responsible for poor or undesired film thickness and bubbles in the e-coat tank. Instrumentation systems failure. This failure causes lack of process parameter compliance, use of improper temperatures and imbalance of dehydration levels in curing and baking oven.
2.2 Problem analysis The tow bar will be used here in the analysis of the problem since it is main product processed on the Paint Line. If the abovementioned production process was theoretically flawless, the Paint Line is capable of producing its targeted 1500 tow bars per 12 hours per day, which means 125 tow bars in an hour. This figure
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can be translated to 7500 tow bars per 5 days or 60 hours available time. The approximated average factory sale price of a tow bar is about of $440. Thus the Paint Line is capable of producing product worth $660,000 in a 12 hour shift. The financial hourly breakdown would then be (125×$440)= $55,000 per Hour or $916.16 per minute This also means that a stoppage of 1 hour on the Paint Line would cost the organisation $55 000 or $916.16 per minute. It is necessary to lower down the cost of production per unit so that Trimas remains very competitive in the market. The Paint Line has not yet reached the level of productivity required as specified by the equipment manufacturers and installers (OEM) namely Garnic Technologies and Luxford Conveyors respectively. It was running at between 40 to 49% or producing about 600 quality tow bars per day. Several problems were responsible for the reduced efficiency of the whole Paint Line system. To quantify the problems this author designed and printed some Paint Line Availability Log sheets that were used by production operators to log in failures or problems, date and time of failure and time when the plant would be back for production. The log sheets also showed whether it was maintenance or operators who had rectified the problem. Appendices A, B, and C show the Paint Line Availability Log sheets. As discussed in Chapter 4 the down time of this plant was at 40%. This downtime and poor plant performance resulted in low productivity prompting the need to develop and implement an optimal maintenance strategy to increase the reliability and availability of the Paint Line. Prior to developing and implementing a strategy it was necessary to find out the reasons why the Paint line was incurring costly downtime and also why its reliability rate was below expectation. Besides this, the quality of the products was another issue which was to be investigated during this research enabling the researcher to find the best possible remedies to prevent quality losses. All these problems impact on the productivity and sales output of the organisation and thus can have negative effects on competiveness of products, supply chain, and overall corporate finances. The overall aim of this research was to analyse ways that assist in increasing the efficiency of the Paint Line to meet the production targets and ultimately the
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Trimas strategic Aspirations indicated earlier in the company’s background and the Quarterly report. (Trimas Corp, 2011). The detailed objectives were to: 1. Analyse why the equipment is basically failing to give the available production time and why it is unreliable. It is necessary that when such an expensive asset is always failing, the maintenance personnel should investigate the how, when, where, what, who of the problem. The root cause of these failures can be detected thus enabling changes to be made. 2. Develop a maintenance and production strategy that combines the effort of all maintenance, production and senior management staff. When the causes of low availability and reliability are identified it is important that management in the maintenance, production and other departments unite to find ways of operating the Paint Line in an efficient manner. The maintenance department would lead in the investigation and harness information from the other departments to develop a workable maintenance and production framework. 3. Develop an implementation plan for change that would enable the improvements and efficiency of the asset. The final objective of this project was to make recommendations and develop an implementation plan to be used as a change management tool. The project would not be complete if a plan for change is absent and also a method of monitoring successes, failures and also fine tuning were absent. It is worth to note that change would encompass the maintenance strategy and organisation, production department operation framework, Paint Line technological changes and the overall personnel behaviours and attitudes.
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2.3. Research Methodology This project offered an opportunity to analyse how industry or manufacturing in general is affected by asset design, maintenance application techniques, management and also the human factors. Previous studies regarding data collection and research on the reliability and quality issues were taken into account. Evans (2008) suggested that data on plant performance, maintenance effectiveness and production output need to be collected as evidence of facts. The research methodology in this project was a combination of Quantitative and Qualitative types. The Paint Line sub-systems were investigated and measured on efficiency and quality, and numerical data was analysed for the performance and reliability of the Paint Line. Human factors that contribute to the performance were also considered and their qualitative effect was taken into account. The problem solving methodology is outlined below in Figure 8.
DATA ANALYSIS DATA COLLECTION
MTTF, MTTR, OEE
OBSERVATIONS. Prepare a maintenance strategy
SOLUTION Maintenance strategy, organisational structure
SURVEY-people, interviews, production records, maintenance records
RECOMMENDATIONS
Figure 8: Methodology Plan used to survey, acquire and analyse data
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2.3.1 Survey and Data collection The methods that were used to collect information were primary and secondary sources as outlined below. Log sheets, written reports, observations and interviews were the general information gathering techniques used in the facility. See Appendices A, B, C, D and E. The collected data was categorized as follows 1). Primary data Information was collected from the Maintenance department on asset history, current life cycle management, maintenance staff culture and organisation. The role of the Original Equipment Manufacturers (OEM) and contractors was of critical importance in supplying information on maintenance activities and the actual costs of their work as shown in Appendix E. Information reflecting on the operational efficiency, specific problems on the Paint line, plant process and skills matrix of the production personnel was recorded. The methods of collecting this information were through production reports, sales records, training and assessments reports and feedback. The financial elements of maintenance regarding cost of production, product prices, maintenance budget, and cost of spares, asset values, maintenance staff wages and training costs were collected by interview with the Maintenance manager, Accounts officer and Human Resources officer and other informal channels. There has always been difficulties in collecting financial information in an organisation, thus the information collected by this researcher must be treated as confidential by readers. 2) Secondary Data Information on Paint Line expected levels of performance (KPIs) was acquired from the actual and also from manuals supplied by the OEMs, journals and textbooks and from the internet. Furthermore information about maintenance models, investigating the root causes of the Paint Line problems and equipment care were acquired
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from electronic and print media. Although possible remedial measures were found through brain storming at meetings, helpful information to solve the problems could be sourced in books, journals and case studies 2.3.2 Data analysis In the analysis of the data, the Mean Time to Repair (MTTR), Mean Time Between Repair (MTBR), Overall Equipment Efficiency (OEE) and Downtime figures were calculated. The purpose was to find out the qualitative information about the overall plant healthy. Primary data is not helpful if it cannot be interpreted or decoded. Thus methods of data analysis like bar charts, histograms, Failure mode Effect and Criticality Analysis (FMECA), the Pareto analysis, Ishikawa, Root Cause Analysis, and 5 Whys will be weighed for suitability as investigative tools in this thesis. 2.3.3 Observations After analysing the data some observations were made. The factors that influence OEE, Reliability and Availability were found to be below expected rates and could not support high productivity. In addition to that human resources and organisational structures could not enhance an environment conducive for worker productivity and motivation. Thus the organisational structure and maintenance strategy were pointed out as immediate areas in need of corrective action. 2.3.4 Recommendations After analysing the Paint Line’s critical equipment on the causes of low availability and poor performance, recommendations to solve these problems were made in Chapter 5.
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CHAPTER 3 Literature Review
3.1 Introduction In its varied applications, maintenance covers various areas in everyday life. Roads, dams, ports , bridges, railway lines, machinery, automobiles, power stations, sporting facilities and buildings all need to be maintained, restored to their original working state and continue to be improved. In all assets mentioned above there are fundamental metrics that maintenance practitioners and engineers, and business managers link for the upkeep and sustenance of these assets. This Literature Review will discuss the effect of these important indicators, strategies, theories and how they impact on the health, reliability and maintenance of assets with particular reference to the Trimas Corporation Paint Line. Section 3.4 of this chapter briefly focuses on early history of maintenance and what has been done previously and the relevance of the researchers’ conclusions on this topic. Section 3.7 will deal with theories, models and practices that are used to analyse and prepare the findings of the problems in asset maintenance. Throughout the Literature review, some ideas of maintenance gurus and commentators on this subject of maintenance and the future direction maintenance is likely to take are discussed. 3.2. Objectives of the Paint Line study Trimas Corporation is an organisation striving hard to meet its aspirations and continue to be a leader in the supply of a range of products. The pressure is evident with some competitor suppliers in this market that are baying for a share in the market. Figure 9 shows that the maintenance organisation is pivotal to the enterprise and internal output. This means that cost saving productivity, operational efficiency, and effective and efficient asset management can place Trimas at an advantage if best maintenance practices are implemented. The car industry has been hit hard because of the Global financial down turn since 2008 such that manufacturers like General Motors Holden would have closed were it not for a bailout of $275million by the Australian, Victorian and South
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Australian governments. The closure would have affected 12 000 jobs at GM and downstream in the component and service sectors (Stewart, 2013). More and more money cannot solve today and tomorrow’s problems, but a new philosophy of improved planning, scheduling, maintenance strategies, cost management and personnel motivation can be important keys to solving efficiency and effectiveness issues in manufacturing industries.(Lewis & Nietubcz 2007) 3.3 The Maintenance organisation The Maintenance organisation or department is one of the most critical arm or pillar of a company or enterprise. Figure 9 shows how Kister and Hawkins (2006) interpreted how maintenance facilitates productivity, stimulates high sales revenue and is also responsible for quality and safety. In order to continue to achieve positive results, reliable and healthy assets are required. Reliability has been and will continue to be an important state or condition any designer or manufacturer would want to achieve with their asset.
Labour, Materials, Spares, Information, Money, Spares, Contractors, Tools, Skills, Training & Development, Leadership, Management, Planning
Production System
Maintenance System
Profit, ROI, Revenue growth
Plant availability, reliability, maintainability
Product quality, output safety
Enterprise System
Figure 9 Maintenance organisations, the centre to enterprise and internal output. (Source: Kister & Hawkins 2006)
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In this regard it can be stated that instituting proper maintenance and its systems adds value to assets. It is a cost saver and a vehicle for revenue growth thus its importance cannot be underestimated.
3.4 Early studies of Maintenance concepts and practices Before Reliability became a most sought after word, many organisations were merely concerned with productivity and improving labour efficiency while more focus was on cost reduction. This earlier concept was inefficient. More time and money was spent in trying to force or mould workers into “yoke and harness” of the system before industry managers realized this was of little benefit. Production and maintenance needed a change. In the ‘Historical View of Maintenance,’ Kister and Hawkins (2006) stated that maintenance has not been with us for long times save for the years between the start of the Industrial Revolution in about 1760 AD up to now. This period is compared with the age of the Earth and thus it is compared to be less than 1second in a 12hr clock. In this assertion it is noted that maintenance has been with us and even with other early Hominids (early human beings) considering they used stone, iron and bronze tools which needed resharpening or reconditioning. This theory promotes the idea that Maintenance is evolutionary as much as it is suggested that humans have undergone evolution, thus their needs and ways to do things are always changing for the better. The effect of technological evolution in assets and global economics has also brought in the concepts of different maintenance strategies that will be discussed briefly in the next sub- section.
3.5 The concept of a Maintenance operating process The maintenance operating process was recommended by James and Quinn (1977), and was based on the introduction of production requirements and matching system to decide the maintenance strategies. Although published earlier, this process has stood the test of time and maintenance processes revolved around this with slight variations or modifications. In relation to the Paint Line this means there is need to know potential Paint Line availability, production requirements,
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and current plant status and maintenance history in order to institute a proper maintenance strategy. This relationship has been simplified in Figure 10. Sun (2006), a researcher on this topic of reliability and availability analysed methods and models that can be used to predict reliability rates of complex reparable systems. The Tow bar Paint Line fits well in this category of a complex system, and some models which can also be used for failure prediction such as the Markovian, Bayesian and Poisson methods will be discussed later. Lingamameni (2006) suggested that modelling of an asset management processes can yield more understanding of the problems and remedies for maintenance rather than mere theoretical assumptions and conclusions. On a step closer to ensuring asset reliability, Figure 11 shows the elements that are important in order to execute a Reliability maintenance strategy rather than mere maintenance efficiency or productivity. This diagram offers an overview of the necessary techniques tools, theories, models and strategies required to achieve asset reliability. Its application transforms the maintenance objective into the business objective of the organisation, thus most views in this thesis will be based around these elements.
3.6 Key Performance Indicators Key performance indicators in maintenance are used to evaluate the success of a particular activity or process. A combination of several Metrics or Performance measures produce Performance Indicators that highlight some condition or behaviour, for example, Schedule compliance. Furthermore a combination of several metrics and indicators yield an assessment of critical or key processes to help evaluate various outputs in the maintenance organisation. It is important to qualitatively know how a system such as the Paint Line is performing by measurement. The use of KPI’s enables the assessment initiative of any system. The following critical KPI’s have been taken into account in this research:
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Maintenance system Flow chart
Repairs
Inspection
Overhauls
System Availability
Maintenance History
Corrective Maintenance
Production Targets
Condition based Maintenance
Repairs Maintenance Preventive Maintenance
Figure 10 Flow chart of a maintenance system (Source: James & Quinn 1977)
3.6.1 Reliability Reliability is one of the keywords in this thesis. Kister and Hawkins (2006) described it as the probability that an item or equipment can perform its intended function under stated conditions. In further analysis, Brown (2004) similarly defines this reliability characteristic as the Mean Time to Failure of an asset in a given period. In fact, Brown emphasises the dependability characteristic of an asset as critical. Jaynes et al (1998), as designers and manufacturers of conveyors put the reliability rate of Overhead trolley conveyors similar to the Trimas Paint Line to at least 99%.
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Reliability
Engineering
Maintenence Models
Corrective, TPM, CBM, RCM
Reliability/ analysis & tools
Probability, Bayesian, Weibull, Poisson
Problem solving techniques
RCA,FMEA, FMECA,RBD
Optimisation
policies
Asset acquisition process
Cost based,Risk based, Quality, Production
Figure 11 Reliability Engineering Strategy for the Paint line In view of asset operation capacity, the term Reliability is important as it measures the state of health of a plant. Reliability is calculated as a percentage (%) of stipulated time. Reliability= Mean time to failure ÷ stipulated operating time, There are other formulas for calculating Reliability, but the essence is in the reason why reliability is a critical KPI in asset management. When a reliability rate for certain equipment is calculated, the failure pattern, asset efficiency, production down time are identified thus corrective action is then taken. Smith (2006) in his view on plant reliability also recommended that reliability ought to be the buzzword of any maintenance organisation. However this contrasts with earlier views of Kister and his colleague who asserted that reliability for the sake of reliability was incorrect for business. This author’s view is that certain KPIs like, maintenance costs, unit cost of production, inventory turns, and cost of condition monitoring gadgets must also be taken into consideration to determine
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implementation of reliability strategies. This approach should optimize on the best suitable economical and sustainable method to attain Reliability. McCarthy (2013) stated in the analysis of design for reliability that the cost to correct an asset or product at the manufacturing phase of the life cycle can be more than 10 times the original value. Thus reliability should be considered right from the design stage to manufacturing of a product or equipment. During the manufacturing or utilisation phase, equipment develops problems and downtime is incurred. In order to reduce down time and increase reliability some organisations employ different maintenance methodologies. The Ford motor company introduced the preventive maintenance in the 1920s. Afefy (2010) recommended the use of Reliability Centred Maintenance to arrest asset failures caused by poor planning and implementation of problem solving skills. 3.6.2 Availability Availability is the time an asset is available for production per scheduled time. This is denoted by the following equation: Availability .
= Mean time between Mean time to repair + Mean time between failures
failures
Availability is production oriented, unlike reliability which is maintenance oriented. To explain further, availability is the actual run time of an asset divided by the scheduled production time. Most organisations benchmark the Availability rate to at least 97 % (Mitchell, 2006). Brown (2004) found that Availability together with Reliability was introduced in manufacturing in the late 1990s as a change from Total quality management (TQM) and Business practice reengineering (BPR) because of the need to improve productivity and equipment performance. This KPI is misconstrued by many maintenance practitioners and production management as non- critical since more efforts are turned to productivity and the less effective strategy of Preventive maintenance. Brown addressed this short sightedness by explaining that calculation of the required Availability rate of an asset was important in determining maintenance custody plans, production plan and sales forecast. Thus it is important that all management in maintenance and production should not underestimate the impact of this KPI as evidenced by Availability Log sheets in Appendices A, B and C. The advantage of
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knowing the Availability rate is it provides an opportunity for instituting an intelligent strategy for operations uptime and maintenance downtime. This process suggests that necessary equipment for production and quality needs should be identified and repaired or overhauled well in time. As an indication of the importance of availability, some programs and software that can be used to record asset availability like Asset Management’s SystAid software and the MEX CMMS have been developed. They are important in the evaluation of availability rate of an asset. 3.7 Asset assessment and investigations Reliability and Availability cannot be achieved without following a process or methodology. The process requires fulfilment of stages and answers at certain steps before maintenance strategies are implemented. In this subsection, some very important methodologies and investigative processes that are used to find the very problems that cause asset failures come under analysis. There are different types of methodologies. Some are logical or systematic methods while some are based on calculations and the laws of probability. The importance of these methods are that they are used to reveal the root causes of problems, or estimate which part or asset might fail before it actually fails so that corrective action can be taken early enough. There are a number of investigative and assessment tools or methods, and selecting the right method can help resolve failure problems or predict failure in a system. Examples include Ishikawa Fishbone, fault tree analysis, Kepner-Tregoe method, Human performance evaluation, and Events and casual factor analysis. However for maintenance and asset reliability purposes the relevant following methods were analysed. 3.7.1 Root Cause Analysis This method is one of the most commonly used processes and is used to pinpoint the exact cause of a problem in maintenance. When the cause of the problem is determined then engineering modifications or any suitable corrective action is applied to eliminate recurring failure. Kister and Brown (2006) stated that failures usually take production and maintenance personnel by shock! However finding the root cause delivers a solvable problem and removes the mystery of failure. Root cause analysis is instituted in 5 phases, which are as follows:
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a) Data collection The data is collected when a fault occurs. The information includes conditions before and after failure, environmental effects and persons involved. b) Assessment This involves identification of the problem, determining significance of the problem and conditions at and before occurrence. c) Corrective actions Implementing corrective actions for each cause reduces the probability of recurrence. d) Recording and brainstorming The results of the RCA must be recorded, discussed with management and personnel involved interviewed. e) Follow up and review The follow up determines that corrective action has been implemented and failure is not recurring anymore. Kister and Hawkins (2006) and Latino (1997) agreed in that RCA was very important in failure analysis but it would not succeed if personnel lacked support from management, lack of discipline or integrity, lacked knowledge of the asset operation and its critical parts. It would neither work also if there were inconsistencies in documentation and reporting of data. On the other hand Kister and his colleague emphasized on the need for personnel to be trained, developed and also be motivated as an incentive to harness their efforts. In a survey conducted by Plant Maintenance Resource Center in 2009, results showed that 79% respondents used some form of structured RCA Method and their benefits were an increase Availability and Reliability (Plant maintenance resource center 2012). 3.7.2 Failure Mode and Effect Criticality Analysis (FMEA/FMECA) The Failure Mode and Effect analysis (FMEA) was also reviewed as a problem solving technique. This term defines a process used to determine the failure of an asset by finding out which parts have failed, why they have failed and the effects of their failure in the system. Kister and Brown (2006) defined failure mode as the reason or cause of a failed item on the asset and stressed out that maintenance
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workers needed to understand different failure modes which reduce availability of their assets. This is done through recognizing symptoms and traces of how these defects develop. In this view it is worthy to note that plant or asset knowledge and experience is very important for the maintenance workers. In detail the function of the asset in the system must be known together with its components, power ratings torque, output and operational condition. This brings in the idea of training the maintenance personnel on plant systems and operation which enables them also to perform fault diagnosis. Kelly (2007), promoted the idea of drafting a Maintainability Diagram which enables enhanced identification of failure modes of assets. This diagram simplifies the overall view of the asset’s components and also their functional criticality. Figure 12 shows the Maintainability diagram of the e-coat pump based on Kelly’s model. E-coat rinse pump
Output pressure gauge
Electric motor
Pump
Rotor
Impeller shaft
Motor bearings
Mechanical seal
Figure 12 Maintainability diagram of the E- coat system pump. An analysis of Figure 12 reveals the components or parts that can fail. In this case the e-coat rinse pump will not be stated as failed. The failure mode can be either in the electric motor stream or pump stream. Thus instituting an investigation would require a start point from checking the pressure gauge, then to electric motor and consequently to the pump.
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Failure modes were also identified by Weber (2005) and were classified into certain categories as follows: a) Hidden consequences- This implies there is no direct cause by a single point failure other than exposing the system to secondary or multiple failures that can be identified physically. b) Safety consequences- This failure causes equipment damage, injury or loss of life. c) Environmental consequences- A failure resulting in environmental effects. d) Operational consequences- A single failure point with effects on productivity and quality. e) Non- operational consequences- A failure resulting in cost of repair only. Thus FMEA uncovers the failure mode and then assesses its effect in the system or asset. Its advantage is that basic training can be achieved for delivering results and can be used in any stage of the life cycle an asset.
3.7.3 Fault Tree Analysis The Root cause analysis (RCA) technique is used in Reliability and Safety engineering practices to deduct and analyse basic systems condition failure. In contrast the Fault tree analysis method or FTA is used in complex assets such as the Paint Line which has numerous sub-systems and computerized operational networks similarly to aircraft and spacecraft. Ericsson (1999) stated that this top to bottom, deductive failure analysis method was developed in the U.S.A at Bell Laboratories in 1962 by H.A. Watson. The use of this technique to find root causes of failure is more convenient. Ericson further explained that it is a method that models a combination of lower level events that lead to the occurrence of an undesired event or system failure as shown in Figure 13. FTA can be used to identify the sequence of events, identify safety conditions, capabilities of assets, and also identify design defects and needs for modification. In this view the author’s evaluation is that this method is much more effective than just a structural FMECA/ FMEA method. The Fault Tree Analysis (FTA) is a more complex technique needing diagnostic skills and mathematical computational skills.
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Conveyor chain stopped
Chain drive motor failure
Rectifiers tripped
Motor overcurrent
Chain snapped/ jammed
Exit stoppers faulty
De-dogging failure
Faulty tensioner
Figure 13 Fault Tree Analysis diagram for the Paint Line chain (Source: Author) Figure 13 shows that the top event “Conveyor chain stopped” is caused by any of the bottom events and the top event or “undesired state” can not cause any of the bottom events. In his analysis of FTA, Sun (2006) concluded that same level events are also not interactive and therefore independent. This means FTA has limited use to describe interactive failures thus it opens an opportunity to explore a suitable method for interactive failures in future. Since FTA is mostly used in complex reparable assets, this technique needs training on how, when and where to use it for optimal benefit. Basic failure modes, failure rates and failure mechanisms must be understood when undertaking an FTA. 3.7.3 Cause and effect Analysis (Fishikawa Diagram) The Cause and effect analysis or Fishikawa method, as shown in Figure 14 was originated by Kaoru Ishikawa in the 1960s and has been used in the car manufacturing industry. Kniberg (2009) stated that this method is effective for finding the causes and effects of poor designs and potential problems in plant systems or in a business operation. The causes of the problems were identified as
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variations. Originally 6 categories of variations were named as People, Methods, Measurements, Assets, Environment, and Material. Of late, Management and Maintenance have been added to make the categories to 8.
Management
Maintenance
Leadership
Environment
Pollution Skills
Strategies
Operating procedure s
Methods
People
Process parameter s
Measurement
Efficiency
Assets
Paint Line problems
Paint mixture
Material
Figure 14 Fishikawa or cause and effect diagram. (Source: Mindtools, 2012) The Cause and effect diagrams reveal relationships of different variables. A useful tool that can combine well with the cause and effect method to help solve problems is the 5 Whys Method. Bennett (2008) stated that the use of the 5 Whys is effective in finding the root cause as one continually asks the first 4 “Whys” that reveals the symptoms and the last why would then produce the root cause. Mindtools (2012) explained that the cause and effect method offers a comprehensive process to find and eliminate problems in all the categories of a manufacturing process which implies that it could be used in the Paint Line as shown in Figure 14. Mindtools (2012) summed up the Fishikawa method‘s 4 key stages which were:
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a) Identifying the problem b) Working out the major factors involved c) Identify possible causes d) Analysing the diagram to find the solution This method helps to identify bottlenecks in a process and why the Paint Line is not producing the required 1500 tow bars including quality problems. This method requires lateral thinking and can be used by many crafts people even with less mathematical ability. 3.7.5 Condition Monitoring The abovementioned problem finding methodologies offer a theoretical platform and to some extent reactive methods to solve problems in a manufacturing process, management, marketing, distribution or in general society. Condition monitoring is a practical application of problem solving techniques. It is a real time technique and shows almost accurate conditions of the state of assets or part of it. Condition monitoring includes vibration monitoring and analyses, Thermography, Tribology, Process parameters monitoring, Ultrasonic Monitoring, Visual inspection and other methods. Condition monitoring is linked or attached to Condition Based Maintenance which will be discussed later on in Maintenance frameworks. Condition monitoring rationale Mobley (1990) indicated that surveys on maintenance management effectiveness showed that a third of maintenance costs were as a result of unnecessary or improperly carried maintenance. This implied that the ineffectiveness of management of the maintenance organisation impacts heavily on the quality of products, quantity and loss of production time. Furthermore it leads to production of expensive products thus rendering any organisation to be out of competition. A plant or asset without condition monitoring systems lacks factual data that enables timely decisions to be made for proactive action before the plant or systems breakdowns. Brown (2004) further clarified that Condition Monitoring or CM is a process to find the root cause of an impending failure thus removing the misconception that equipment failures cannot be predicted. Liebler (2005), called it a ‘Maintenance tool’ which can assist not only in identifying impending failures
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but also help in labour organisation and logistics. This supported the fact that failures are now predictable with new technology. Computerized diagnostics and instrumentation can help monitor plant and systems condition and provide ways to reduce unnecessary repairs prevent catastrophic failures; reduce impact of maintenance cost on product quality and production costs. Condition monitoring can lead to increase of the bottom line profit. Challenges of Condition Monitoring It is worth to note that installation of CM instruments can be very expensive thus it needs to be limited only to critical equipment or components of certain assets. Sondalini (2012) argued that condition monitoring is a waste of time and money because of the unreliability of the readings and data acquired to correcting failures and saving money. However, in contrast Brown (2004) cautiously warned of the complacency of most organisations who dedicated most of their time to acquiring and analysing data and not practically correcting the problems after acquiring condition monitoring data. This could have been the cause of Sondalini’s oversight. Most companies who misunderstood condition monitoring were in the habit of installing ‘Christmas tree’ gadgets on a plant and were not employing a Criticality Index to determine critical assets worth to be monitored. This author noted that a properly commissioned CM regime builds a workable PM and CBM and thus saves work force stress, creates proactive action, optimizes planning and scheduling and improves maintenance work quality, production capacity and certainty. 3.7.6 Mathematical (Probability models) Assets are designed differently, and not every organisation is able to buy state of the art equipment that is maintenance free, or trouble free. Complicated and complex assets are the order of the day in these competitive times such that to keep the assets up and running certain measures need to be employed. Sun (2006) outlines that reliability assessment tools offer solutions to gauging the frequency and areas of failures of assets by using mathematical probability models. In this section the Weibull, Markovian or Bayesian models were discussed as alternative fault diagnosis and reliability modelling methods. However, El Hayek (2006) warned that merely relying on mathematical models to solve maintenance
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problems was not adequate as it risked some inaccuracies. In this subsection the Weibull model was analysed. 1) Weibull/Reliability Analysis This method involves the proper application of statistical methods to model failure data and estimate quantities of interest for plant systems and components and thus make predictions for maintenance actions. (Weibull, 1951) In this regard, El Hayek noted the Weibull theory, a method that reveals life characteristics and a defined failure probability pattern of machine components. The Weibull model can be used as a solution in solving maintenance problems with a lot of rotables and complex parts. Abernethy (2006), added with his assertion that the Weibull analysis is effective for engineering analysis even with small samples, two or three failures. F(x)
pdf curve
T Figure 15 pdf curve modelling behaviour of an asset (Weibull.com, 2012) This makes it suitable for aircraft safety analysis and development testing with small samples without the need to waste more samples or risking lives. The Weibull analysis is a life time distribution model. A Probability density function (pdf) curve is shown in figure 15. The Weibull model of cycle time to failure is given by
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F (t) = P (T ≥ t) where F (t) failure density function, and P is the probability, T is the cycle time to failure. Once the parameters that fit a life time distribution to a data set have been calculated, plots and other results can be obtained including
Reliability given time Mean life Failure rate Warrant time B(X) Life-A specified Reliability rate e.g. 90% during warranty period Reliability- Time plot Failure –Time plot graph Probability of failure given time.
Limitations of the Weibull model The Weibull model as a formidable tool is used to measure and speculate plant healthy and define the possibilities of failures. However, Lingamameni (2006) stated there were limitations of mathematical models in solving root causes to assets. This was based on the problem of estimates and uncertainty with this method on collection of failure data and choice of distribution used. Thus inadequate failure data and an incorrect distribution can cause a difference in the authenticity of the results from the analysis of the plots and calculations. The other probability methods will be explained in brief in the following paragraphs.
2) Bayesian Model This is a statistical probability model that was introduced by Pastor or Reverend Thomas Bayes (1764) to solve estimates of events or failures happening. The model anchors from a prior chain of events and builds on the current to estimate the probability of prediction of direction of an event or failure. Sun (2006) added that for the success of this model, prior information that includes data from designers, engineers and maintenance or production workers or the general history of the plant or asset is required. Its limitations are in the data collection and
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confidence intervals that can cause variances in results to be analysed to predict reliability and availability in equipment. Walsh, (2002) in the Introduction to Bayesian Analysis stated the analysis of the posterior data distribution of certain parameters in a plant or asset through this model produced a clearer picture of the unpredictable events when certain nuisance parameters are removed. Prior belief
100
Posterior belief 75
CONFIDENCE RATE %
50 0 25
0 Problem A
Problem B
Problem C
CONVEYOR CHAIN PROBLEMS
Figure 16 Confidence rate data sets of the conveyor chain problems. The Bayesian theorem states: (
(
and (
whereby occurs. ( | events
(
|
( | ∑
are the probabilities that |
(
( |
and
(
occurs respectively,
is the conditional probability that event
when event A
and ( | are the conditional probabilities that event A occurs when and occur, respectively.
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CATERPILLAR DRIVES
CHAIN TENSION
CONVEYOR CHAIN FAULTY (Breakdown)
Figure 17 Simplified Bayesian network for the conveyor chain. Figure 17 represents the probabilistic relationships between the symptoms and problems of the conveyor or the whole Paint Line. The chain tension can cause conveyor chain to breakdown; and also cause the caterpillar drives to jam or mismesh. The caterpillar chain causes the chain to break up or mis- mesh. If the symptoms to these problems are known, they can be used to compute the probabilities of various causes of conveyor chain faults or the Paint Line at large.
3) Markovian Model The Markovian analysis was introduced by Andrey Markov, in 1907 and it looks at a sequence of events and analyses the chances of these events to be followed by one another. In his simplification of the Markov process, Didkovsky (1996) stated that this process is used in maintenance and reliability engineering to predict a new sequence of random but related events that may look similar to the original. In further explanation, the Markov model is useful in prediction of random events or failures that are dependent, meaning the failures are dependent on the likelihood of what transpired in the last event or mode of failure. For example in terms of weather, today’s weather is influenced by yesterday’s weather but not dependent on it.
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Trade skills
Lubrication
Failure modes
Design & develop
Planning & scheduling
Figure 18 Markov random variable field model for the Paint Line. Since a plant system has various parameters like maintenance activities, failure modes in the sub-systems, system management failure, human incompetence and process failure, the Markovian process can be used to determine the effect of all these states on reliability, problem solving and continuous improvement needs. (Sun, 2006) When a Markovian process has discrete time space and discrete state space, it is assumed that conditions or states of any can therefore change. When the change in state of various functions of the plant organisation and the assets change, this can be computed by the Markovian model enabling the reliability of such a system to be determined.
3.7.7. Conclusion of Problem solving tools It is a widely accepted fact that without knowledge of maintenance or plant system and its failure patterns it is difficult to solve its problems let alone formulate
35
counter strategies to arrest impending problems. “A problem well stated is a problem half solved” Kettering C.F (1875-1958). This means problem solving tools and methods stated in this sub-section are critical. Three methods were discussed. The basic methods, the RCA, FTA, and Fishikawa can be used ordinarily for non -complex systems, while the CM tools need investment in buying the necessary gadgets and training personnel in the use and interpretation of data. The other methods stated were the mathematical probability methods. These were the Weibull reliability, Markovian and Bayesian methods. Despite the need for mathematical skills in data computation, these methods can be used to solve complex assets like aircraft and even closely, the Paint Line system. The knowledge and discovery of the root causes of problems is a critical step in the process to attaining Reliability and Availability in any system.
3.8. Reliability Optimisation policies These are maintenance policies that enhance the maximization of a maintenance effort to attain the best possible asset health and reliability at low cost. Sun (2006) and Brown (2004) stressed out the importance of documenting and analysing maintenance costs. In this view, Sun concluded that all costs of repair, spares, and labour and production costs, modifications and stoppages must be accounted for while Brown indicated that base costs such as the following need to be collected frequently: Costs of maintenance hour It is the hourly pay of a maintenance worker added to other items like leave pay and, overtime and other befits to make the standard Labour rate. This cost is well known by most financial managers but is not taken as critical by maintenance management. Brown (2004) found that the advantage of practicing the estimate of this cost can reveal hidden costs in work orders or jobs that might seem simple but are actually costly. Total maintenance cost This is another direct measure of maintenance performance estimated at less than 10-15%. Maintenance effectiveness and efficiency have an impact to this metric. In order that maintenance costs go downward, “The right work
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at the right time should be done.” Weber (2005) recommended the use of Proactive maintenance which intervenes on equipment before failure and increases wrench time to between 40-60%. This is great saving on catastrophic failures and also secondary damage. This concludes that efficiency in reducing maintenance costs is through proper work planning and scheduling. Cost of individual equipment This KPI assists in keeping track of costs associated with individual equipment as a measure of its performance and availability, reliability and cost of maintenance Total contract costs This value is estimated at between 35-64% of the total maintenance cost. It is worthy to note that when contract costs exceed the marked threshold, contract revision and evaluation should take place. Cost of production Maintenance costs, raw materials, wages are all factors of production costs thus plant availability, and down time affect production costs. Thus it is necessary to minimize cost and optimize the resources in order to produce competitive products. Book value of facility or equipment This is the cost of building or equipment including installation less the depreciation value of the asset. The calculation of this value was contended by Brown (2004) who stated that it lacked integrity through the way it was calculated. However he noted that maintenance and repair costs skyrocketed when capital replacement was stalled and finances are curtailed.
These indices are collected for the purpose of evaluating maintenance efficiency and effectiveness, and in future these would determine the direct actions to be taken to raise the availability and reliability bar.
3.9 The risk factor in maintenance A major concern to plant assets and personnel besides Reliability and Availability is the risk factor. The risk of losing product through poor quality, lost time injury,
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damage to machinery and environmental effects is quite obvious. Maintenance is a business and can generate profits in an organisation if optimal care is taken to reduce likelihood of the above losses. Inclusion of Risk management principles will also determine the maintenance strategies to enhance maximum attainable production time. 3.10 Maintenance Frameworks This sub-section will discuss some commonly used maintenance methods in the world and how they can be applied to the Paint Line to attain the required level of reliability. Maintenance frameworks, also called methodologies are processes used to conduct maintenance through certain theories and methods. Frameworks differ from organisation to organisation and some continue to evolve. 3.10.1 Introduction Maintenance is established not only with the objective of lowest maintenance cost but lowest cost per unit of the product (James & Quinn 1977). This view was also shared by Brown, (2004) in his “Defining the level of Maintenance” where he stated that a quality product for the sake of quality with no bottom approach was bad business. He further stated also that reliability for the sake of reliability was also retrogressive. However it is important that a maintenance framework must suit the business end of the organisation while optimizing on quality, safety and the environment. In determining the type of maintenance framework Kister and Brown (2006) acknowledged a study by the FAA/ Airline Industry Reliability program that was investigating the failure pattern of equipment or components. As indicated in Figure 19, different equipment tends to follow a variety of failure probability.
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Is failure affecting equipment, health & safety Is failure impacting on productivity/ quality
YES YES
NO
Is failure affecting cost, damage or systems
YES
Employ effective PDM technology
NO YES Develop & schedule PdM task to measure condition
NO Is there internal effective based task
NO
YES Develop condition monitoring task/ method
Develop time based task/ method
Redesign system / equipment
Operate to failure
Figure 19 Maintenance task determination pattern (Kister et al, 2006) BCM- Business centred maintenance RCM- Reliability centred maintenance PdM-Predictive maintenance PM-Preventive maintenance. It is important to realize that due to the complexity of assets, some organisation can use a combination of different frameworks to suit their maintenance requirements. The choice of a framework is also dependent on production, seasonal sales or peak
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demands. The different types of frameworks will be explained in the following subsections. 3.10.2 TPM- Total productive maintenance This is a maintenance philosophy that extends the idea of preventive maintenance effort through self-directing and autonomous groups of production staff and maintenance staff to perform maintenance on assets. Kister and Brown (2006) extended this description by stating that the goal of TPM is to advance the “profitability” of PM and reduce prospects of unplanned maintenance, accidents, breakdowns and defects. TPM, originally from Japan in the late 1980s is a strategy that needs the active support of all managers, executives and supervisors for its success. According to Kister et al, the KPI which measures the effectiveness of TPM is Overall Equipment Effectiveness, OEE. It is expressed as follows: OEE= (Equipment Availability) x (Performance efficiency) x (Rate of Quality) World class benchmark of OEE is ~85%, which is derived through the following values: 90% (Equipment availability) x 95% (Performance efficiency) x99% (Quality rate) =84.6 OEE. It is worth to note after analysing the Trimas commissioning shutdown document Appendix E and Daily Paint Line availability log sheets Appendices A, B and C, that many problems the Paint Line have are a result of lack of preventive strategy. In this perspective it is also noted by Kister et al that the abovementioned problems are classified as the 11 major losses that TPM seek to eliminate, which are as follows: 1) Planned shutdown losses -at breaks -at shift changes -at planned maintenance 2) Performance efficiency loses -during minor stops (1-6mins) -from reduced production speed
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3) Down time losses -from breakdowns and equipment failure - Changeover/ part or tool changes -during start up and adjustment 4) Quality losses -poor product/ scrap -defects/ reworks -during process transition Davis (2011), in ‘The analysis of TPM 20 years on in the UK’ noted that there were 5 pillars of strength for TPM to succeed which were; establishing a total preventive program; involvement by all employees in operations, production, maintenance and management; motivation; optimizing on OEE and involve all systems of operations, maintenance and engineering Davis consented that its failure was attributed to the lack of buy-in by senior and middle management, and lack of determination and long term vision by those implementing it. Since the other pillars were concerned with human behaviour and culture change, TPM may be effective on assets with cooperative employees but difficult in unionized workforces. Another maintenance strategy that countered TPM as the axe fell on companies during the 1990s Economic Structural Adjustment Programs or ESAP is discussed in the following section as an alternative in maintenance that can be applied on the Paint line. 3.10.3 BCM- Business centred maintenance This is a maintenance methodology that is based on management principle. It identifies business objectives of an organisation, and translates them to
41
maintenance objectives making this as the firm basis of the maintenance strategy policy formulation (Kelly, 2007). This approach differs from BPR (Business practice re-engineering) a process that overtook TQM by eliminating non value activities, streamlining, eliminating waste and implementing staff reductions for the purpose of profitability (Brown, 2004). Production mission
Business objective
Maintenance Objective
Maintenance control system
Maintenanace Life plan & schedule
Production & equipment needs
Work planning system
Adminstrative structure
Figure 20 BCM Thought Process (Source: Kelly 2007) Kelly (2007) identified that mapping out the maintenance strategy of a complex plant and auditing its elements using well established management principles was fundamental to developing a BCM. The BCM was based on the Strategic Thought Process as simplified on the Figure 20. Based on its structure and process, BCM is critical in aligning the objective of production at lowest resource cost. Hughes, (2001) supported this methodology and pointed out that reducing the gap between manufacturing costs and maintenance costs was ideal to making maintenance a “profit centre” than a cost centre. This author concluded that BCM was cost centred, where the buzzword would be “dollars first” as a benchmark for any decision. In terms of financial profitability, this would be suitable but its full application can lead to compromise
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on safety, environment and quality as did Business Practice Re-engineering or BPR (Brown 2004) in the 1990s wave of industrial downsizing. BCM requires additional support systems in training of maintenance personnel, early equipment failure prevention, and improvement of process and maintenance personnel efficiency including the analysis of monthly and yearly budget reports to assess improvements on spending.
3.10.4 RCM- Reliability centred maintenance In the study of Maintenance planning and scheduling, Brown (2004) found that the result of deficiencies of TQM and BPR was the movement towards equipment reliability. Reliability centred maintenance is a methodology that focuses on the need of asset overall reliability by identification of those actions that will reduce probability of failure and are cost effective. It involves a mix of simple preventive actions, condition based and run to failure approach. Besides these issues, Putt (2010) outlined other issues that affect reliability as the initial design and installation of any equipment. The Society of Automotive Engineers (SAE) developed a standardization of the RCM process to define how a maintenance approach could be established for an asset. The findings were as follows: Functional failure Modes and effect analysis (FMEA) 1) 2) 3) 4) 5)
What are the functions and associated performance rate of the asset? What ways can it fail to achieve its required functions? What are the causes of failure? What happens when each failure occurs? In what way does that failure matter? Maintenance strategy 6) What can be done to avoid or prevent that failure? 7) What can be done if proactive task cannot be found? In his analysis of RCM, Sondalini (2012) stressed that this strategy worked very well in industries where the workers were highly disciplined and motivated, a good corporate culture and well- defined business processes. RCM uses condition monitoring to identify the Potential failure point, “P” before an asset functionally
43
fails at “F” as shown on the P-F Curve Figure 21. It is important that point “P” is identified and action taken otherwise Breakdown maintenance becomes the default strategy.
P Performance
* F *
Time in hours or days Figure 21 P-F curve or degradation curve of equipment (Source: Sondalini, 2012) Thus RCM is a process used to determine what can be done to ensure that any physical asset continues to operate in its present state. The short coming of RCM is in the context of trivializing of labour efficiency and waste elimination. However RCM promotes the idea of Reliability engineering for the establishment, organisation and execution using CMMS, Emergency and unscheduled reports, planned and preventive reports, Condition monitoring and Predictive maintenance analysis. 3.10.5 PdM- Predictive maintenance This is a maintenance methodology that compares test measurements against established or benchmarked limits in order to determine corrective action well before failure has occurred. Predictive maintenance also involves the use of human senses to see, feel and sense noise and abnormal conditions while remote sensors, thermograph, contaminant testing and vibration analysis are some of the methods used in condition monitoring. Predictive maintenance is mostly twinned
44
with planned preventive maintenance as an implementation plan to ensure the results are fully utilized. Its advantages were stated by Humphrey (2007) as strategic in that, information from knowing the condition of the assets could be used to anticipate repairs, order parts, schedule resources and minimize stoppages. Normal accrued stoppage time through time based preventive strategies or breakdowns or even catastrophic failures can be avoided. Lewis (2007) acknowledged that Predictive maintenance worked well for critical assets and not on each and every asset in the plant. The consideration for items to be monitored included the cost analysis in terms of: Criticality of equipment Cost of repair or replace Cost of down time Past maintenance history Cost of monitoring versus benefit Condition monitoring needs a structure to be set up. There has to be a trained workforce, selected equipment, selected technologies, selection of instrumentation, then selected alert levels and measurement of the effectiveness of strategy and condition monitoring program. This strategy boosts up availability of equipment, increase safety and will reduce costs. In his presentation paper Jonsson (2005) stated that the difficult part in implementing condition monitoring technology was its acceptance by corporate management who focused more on production whilst misunderstanding the value of equipment reliability and availability. Furthermore Jonsson (2005) claimed that plants without proper Predictive maintenance strategy faced difficulties in achieving an OEE of at least 90%. He sighted that through condition monitoring, any availability increment of 1% could translate to 15-20% of savings in maintenance cost. 3.10.6 PM- Preventive maintenance Preventive maintenance is a cyclic maintenance method or time based method. It is carried out from results of inspection, testing and or by manufacturers recommendation. This is often done as a programmed routine. The maintenance department is given the custody of the equipment to perform these tasks. Kister and Hawkins (2006) found out that the increase in production time by the Ford Motor Company between 1908 and 1913 in which car production went up from
45
100 cars to 1000 per day was a result of planned preventive maintenance. In comparison with the Paint Line, preventive maintenance or PM would be suitable as maintenance strategy for non- critical reparable items.
R Failure rate
Cradle mortality
U Failure rate increase
Normal operation
S
T
Equipment age (Time) Figure 22 Bath Tub curve characteristic of the Paint Line Mobley (1990) maintained a similar belief with most authors that preventive programs were time driven or based on hours of operation. This means it would be impossible to increase the reliability of the Paint Line based on timely maintenance. The Bath tub curve RSTU, Figure 22, indicates that a new asset like the Paint Line suffers from high failure incidents due to installation problems, design defects, coupled with the inefficiency of inexperienced maintainers and operators during its infancy period. The curve RS represents a condition known as Worst New in terms equipment condition. Reference was made to Paint Line Availability Log sheets A, Band C showed this failure pattern. The Mean Time before Failure for this asset was averaged at 45minutes which could be represented by ST on the curve. The main conveyor chain was best described to be in the cradle mortality range even after
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breakdown repairs. Other parts of the Paint Line like the pumps and oven fans are on the TU zone, which is the fast failing and wear-out zone. This author observed from the experience in Steel Mills and Mineral concentrators’ plants that preventive maintenance tended to disrupt production unnecessary when there could be no risk of failure. The possibility of inducing failures through dismantling and assembling or merely replacing a good bearing with a new bearing from the shelf cannot be underestimated. This is called over- maintaining assets. This leads to wasted time, resources and lost production. The old style preventive maintenance that involved inspection, lubrication, minor adjustments without predictive analysis and proactive action is by cost analysis risky and expensive on critical assets but optimal on non- critical assets.
3.11. Conclusion of the Literature Review This Literature Review showed that the maintenance organisation is the centre of any enterprise and its internal output. From early maintenance practices, it has been shown that maintenance evolves due to the needs and technological advancement experienced by this world. Practices such as PM, PdM, Proactive maintenance and the default Run to fail have been implemented by various organisations. The growing concerns of competiveness and cost efficiency have introduced Reliability and Availability as critical in production and maintenance year by year. It is important to note Reliability and Availability levels are not just obtained by basic strategies of preventive or design out maintenance alone. On a corporate view organisational fundamentals and maintenance policy restructuring processes should be addressed before Reliability takes root.
3.12. Evaluation of current state and ‘Gap’, inconsistences Kister and Hawkins (2006) noted in the study of RCM and other related studies that the concept of time based maintenance was expensive that all components do not follow the ‘operate reliably and then fail mode’. All components follow
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different failure probabilities. It is important to consider the failure probability distribution pattern shown in the maintenance task determination diagram in Figure 19. In light of this, the study by Sun (2006) and Zhou (2010) on methodologies and models used to predict failures of reparable assets and the degradation process of assets showed how important it is the need to know or acquire data related to failure prediction. Maintenance practitioners need to assess and investigate failure modes and failure causes for them to institute the right strategy or corrective action. In relation to this, different basic investigative methods like RCA, FMECA, FTA, Fishikawa method and Condition monitoring were discussed. Also discussed were the mathematical probabilities modelling methods, the Weibull reliability analysis model, Bayesian and Markovian models. These methods can be applied selectively although some training and mathematical computational skills are required. Their importance in this thesis is to show that despite basic problem solving methods like RCA and FMECA, probability modelling offers an alternative. Zhou (2010) suggested that they can be used to predict the degradation process of assets or components with the assistance of condition monitoring data. Sun (2006) used the probability models to predict interactive and multiple failures of complex reparable systems. Similarly Sun also used real life data and condition monitoring data. In maintenance practices, the concept is consistence in that without knowing the problem or its cause, it is difficult to solve or implement any strategy to eliminate it. Basically it means for a problem to be solved it has to be known that it exists by its nature otherwise time is consumed on fighting symptoms. When the cause of the problems is laid bare, suitable maintenance strategies or frameworks can be implemented. This Literature review explained the different maintenance methodologies, TPM, BCM, PdM, OTF and PM. It is this author’s view that a single methodology does not fit the asset or plant care needs for a plant such as the Paint line. A combination of methodologies to suit operating needs, criticality of assets and optimisation of production and maintenance costs plays a major role in the choice of asset care plan. These were some of the identified consistencies that were noticed during the study of maintenance methodologies.
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CHAPTER 4 SOLUTION TO THE PROBLEM 4.1 Introduction The solution to the Paint Line problems has been determined through analysing the collected quantitative and qualitative data and making inferences in the context of increasing reliability and availability. Performance metrics, Mean Time Between Failure (MTBF), Mean Time To Repair (MTTR) and Overall Equipment Efficiency (OEE) were used to measure the performance of the Paint Line. Human factors were also taken into consideration. Two major factors, organisational structure and maintenance strategy were found to be influencing poor availability of this plant. No solution can be implemented without considering the human resources effect in maintenance. In order to deal with production oriented equipment, critical assets in the system and their respective failure modes were analysed. In the quest for developing and implementing a reliability care plan, suitable strategies were identified. It can be drawn then, that reliability is affected adversely by three main factors, maintenance, poor equipment operation and knowledge, and thirdly poor design. Acceptably, it is the people or humans who are responsible for the design, manufacture and maintenance of machines. Thus it is the lack of control policies, procedures and systems that make machines fail leading to low productivity levels.
4.2 The Human effect in attaining Reliability It was identified that the current performance level of the maintenance and production staff could not deliver the required targets of 1500 tow bars per day. Human factors have been identified as major a cause in equipment failures. Table 1 shows the score rating that will be used to measure personality traits and performance of humans in the organisation. Each factor has been scored against a total of maximum 100% points.
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Table 1: Score rating for humans in the organisation
Score 100 90 80 70 60 50 40 30 20 10 0
Description Above best practices Excellent Best in peers group Better, Fair achievement Potential for improvement Develop and improve Need to improve on Major needs for basics Exists, but never known Does not exist
4.2.1 The effect of various human factors in the organisation This sub-section explains the various effects and shortcoming of the human resources in the organisation against specified traits and performance measures. Based on the criteria given in Table 1, the score of different groups of human resources have been scored as shown in Table 2 and a brief explanation of what they are expected in their roles is as follows: a) Production Operator Paint Line operators are responsible for running the plant, cleaning and identifying early equipment problems and inconsistences through Standard Operating procedures. Some of the attributes of operators include the knowledge of process parameters and quality requirements. The score was 370 points. b) Maintenance staff The skills, behaviour and attitude sets found in this category varied depending on the type of role one has in the maintenance organisation. Trade staff skills were more likely to affect the execution of tasks and are to some extend
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responsible for quality maintenance work through their attitude and knowledge. The more they are skilled the more efficient they are and thus less down time. The score was 360 points. Table 2 Human resources scoring.
Element
Performance output Motivation Systems & work control People culture Technology Knowledge Skills Sense of ownership Problem solving initiative Goal oriented Total
Production operators
Maintenance OEM/ trades contractors
Maintenance Management leadership
60
50
70
40
30
30 30
30 40
60 60
50 30
30 20
40
30
40
20
30
20 30 40 30
20 30 40 30
60 70 60 70
40 50 50 60
40 30 40 50
20
30
50
40
50
60
60
70
60
60
370
360
610
440
480
c) Maintenance Leadership Both the maintenance and production department suffered leadership vacuum initially. The new management were assumed to be on a learning curve and their styles of leadership were yet to be proven to suit Paint Line productivity. God maintenance leadership traits and skills were required to lead and direct maintenance activities in terms of maintenance productivity, labour utilization, lowering the wrench time, safe maintenance practices, motivation and discipline. The score was 440 points.
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d) Original Equipment Manufacturers (OEM)/Contractors Luxford and Garnic Technologies, the OEMs and contractors play an influential role in the provision of services and directly determine the outcome of plant maintainability and reliability. Both contributed in the design and installation the Paint Line plant. Their commitment to plant reliability and cooperation in correcting problems was rated in the score sheet. The rating was 440 points. e) Management Management have the duty to lead, plan and control the resources towards the organisation’s objective. They have to be people oriented, production focused thus knowledge of the systems and process of production and maintenance is critical. Motivation and organising an optimal strategy is a prerogative. Employee motivation is one of the most important factors that help improve worker health, safety and productivity. The results of low motivation are absenteeism, sick leave and lack of initiative. The score was 480 points
4.2.2 Observations It was identified that a change in the organisational structure was needed across the whole production and maintenance departments. The reasons were as follows. 1) Most of the production personnel were not familiar with the plant except for 1 or 2 who assumed team leadership roles. Some of the operators were failing to follow proper operating procedures and sometimes failed to recognize process problems. Thus, the production operators needed to be trained or at least be locally certified by a professional training and development organisation. 2) Most of the production staff were assigned to work only on specific parts of the plant thus could not get experience elsewhere. A rotational scheme would widen the knowledge and skills of the operators into Self- empowered plant operating teams (SEPOTs) who will work together with maintenance staff.
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3) The Paint Line administrative structure was still not clear on who was responsible for managing staff and productivity. A clear structure was overdue to drive organisational goals and policy. 4) Because of lack of skills and separation of roles some operators had become resentful, uncooperative, and morale had gone down. Maslow’s hierarchy of self-actualization and esteem could not be overstated here. 5) It was imperative that maintenance and production staff undergo performance evaluation and skills assessment on a monthly basis and caution was to be taken to update skills and train and develop areas where deficiencies have been identified. At the end of evaluation, proper motivating benefits can be awarded. It can be concluded that the production and maintenance organisation management together with OEM and contractors worked in a disjointed manner. The current organisation structure was just there in name but was ineffective. The high rating of the OEM and contractors imply their commitment to justify the suitability of the equipment they supplied and their services as contractual obligations. Similarly the management also have a higher sense of ownership as they also need to justify their expenditures on this equipment. Remember the shareholders. The maintenance staff and production workers bear the ultimate brunt as shrewd tactics are used to force productivity and an unattainable plant reliability rate. It is also concluded that through these observations there are missing key personnel, systems and processes that affect the plant efficiency delivery. This requires a change in the organisational structure. The new structure is shown in Figure 26.
4.3 Mean Time Between Failures (MTBF) According to Appendix A, the Paint Line incurred loss of scheduled production time as a result of different equipment failures at different times. The MTBF was calculated to quantify the reliability of the Paint Line as a repairable system.
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MTBF is denoted by the formula: Ѳ = Total time ÷ Number of failure On the 23rd of June 2013, Appendix A: The total net available time was 9.5 Hrs. after lunch break and tea time of 1hr was removed In this case the MTBF was 9.5hrs
= 38 mins.
Similarly on the 24 of August 2013, Appendix C, the MTBF was calculated as 11hrs÷16= 38.8mins after removing 1 hr. for lunch and tea breaks These figures indicate that the Paint Line was likely to have 1 failure every 38 minutes in operation. The mean time between failures needed to be increased. As shown in Appendix C and A, there were various reasons for the number of stoppages namely: 1. 2. 3. 4. 5. 6.
Shot blaster communication error Conveyor no. 3 overload trip Conveyors no.1,2 and 9 stopped Unload entry diverter faulty on conveyor no.7 E-coat rectifiers tripped Conveyor no. 7 return over torque
4.4 Mean Time to Repair (MTTR) The MTTR is the time or duration it takes to return equipment into production after a breakdown. It is a basic measure of the maintainability of a system or equipment. In this case maintainability means the degree of effectiveness and efficiency of diagnosing problems and performing corrective actions in the specified time at low cost. Thus MTTR can imply that there are several shortcomings within the maintenance department. MTTR = Length of breakdown period (T)
number of breakdowns (n)
In this case Appendix C, dated 24 August 2012 was used to find the MTTR, thus,
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Total sum of time of breakdown period= 267 min or 4.45hrs lost time The total number of breakdowns= 16, thus 267 16=16.7 min MTTR Thus it has been revealed that the MTTR of the Paint Line for that given day was 16.7 minutes. This also means an average of 16.7 minutes was taken to fix repairs. This loss of production time is explained as follows: a) Maintenance staff inefficiency: This means maintenance staff spent time working on the line only to operate and fail again. Their abilities and problem solving skills were questionable. b) Production staff: By analysing some of the problems on the Appendices A, B and C it can be drawn that production staff operated this plant without full knowledge of its Standard Operation Procedures (SOP) and operating parameters in order to maximise productivity and quality.
4.5 Downtime Downtime is the time equipment becomes unavailable due to failure during a scheduled production period. Again data from Appendix C, dated 24 August 2012 was used to find the downtime thus, Total sum of time in breakdown period= 267 min or 4.45hrs lost time Thus down time can be indicated as %, 267mins
(11hrs 60) =40.4%
There are several reasons for this occurrence as the failures are analysed. The reasons range from plant design, human resources ability, the organisational structure, and an ineffective maintenance strategy.
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4.6 Overall Equipment Efficiency Plant equipment or a production system’s performance is measured by Overall Equipment Efficiency or OEE. Sample day 24 August will be used for finding the OEE of the Paint Line. The formula is as follows: OEE = (Equipment Availability)
(Performance Efficiency)
(Quality Rate)
Equipment availability= (Total scheduled time Downtime)
Total scheduled time
1 0.404 .596 Or 59.6% Performance efficiency Number of units produced per shift
Number of units scheduled to be produced
From Chapter 2 on problem formulation, it was indicated that the Paint Line was producing 600 tow bars instead of 1500. Thus the performance in terms produced units is 600 0.40 or 40%. Quality of output units produced
Number of units produced at quality standard Total number of
600 635 0.9448 or 94.5% Thus the OEE Equipment Availability Performance efficiency Quality rate 59.6 40 94.5 22.5% Calculating the OEE enables screening of major losses that maintenance has to eliminate which are losses due to breaks, downtime, performance efficiency and quality losses.
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4.7 Data Interpretation The data captured and analysed showed that there were some shortfall in factors that were responsible for increasing productivity and maintainability of the equipment. The pattern exhibited by the data showed that breakdowns occurred more often in the morning and the production process was interrupted after an average of 38 minutes in operation. This indicated a low reliability rate and points to a strong need to a change in maintenance strategy. The MTTR of the line was found to be 16.7 minutes. However it is the number of breakdowns that interrupt production in that 12 hour shift that is of concern, Furthermore the downtime of 4.45hrs or 40.5% reveals a special requirement that needs to be undertaken in order to arrest this phenomena. The cause of downtime points to two elements in maintenance. The priority is to increase productivity at low cost. In order to ensure this priority is met the two elements to be dealt with have been identified as change in the maintenance strategy and organisational structure. The Overall Equipment Efficiency, OEE rate of 22. 5% is unacceptable by any maintenance or business standards. It is recommended that the factors that contribute to OEE be analysed. By applying the changes to maintenance strategy and organisational structure, it is expected that Trimas Corp will notice a change primarily in the OEE, increase in uptime; and efficiency and effectiveness of the maintenance department. The necessary recommendations for attaining the above targets are explained in Chapter 5
4.8 The Asset Reliability Stream The Asset Reliability Stream is a logical process of setting up a maintenance organisation to meet reliable or guaranteed levels of capacity, quality and safety on production equipment. The step by step process is illustrated in Figure 23. It has been presented in a simplified form. During implementation, this stream should be continually be evaluated, assessed as it is developed at any stage by the use of the PIE-C method shown in Figure 24.
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The Asset Reliability Stream
Alignment of Reliability strategy to business goals
Develop new organisational structure
Establish Planning & scheduling & spares management
Identify critical assets for bussiness obectives
Develop PM, PdM, inspection & Lube program
Assess,train develop & reevaluate
Establish avalability and reliability rates
Establish work management system
Implement RCA, FTA, Fishikawa, Weibull to problems
Gain Management & team support
Build criticality and general asset list
Implement Continous Improvement cycle-PDCA
ASSET RELIABILITY
Figure 23 Asset Reliability Stream (Ivara, 2012) This process is suitable for use on the Paint Line. The solution was developed by Ivara (2012) and is useful when setting up a maintenance organisation with the objective of increasing equipment efficiency and availability.
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Plan- Identify critical, problematic assets
ControlAssess performance, goals, risk
Reliability
ImproveImplement continous improvement method
ExecutionPlan and schedule execute
Figure 24: The PIE-C method (Source: Pitt Community College, 2012) Kister (2006) identified a similar solution termed the Reliability Excellence (Rx) model used to achieve a truly Lean Maintenance Operation in an organisation. It is recommended that since Trimas Corp has had its own maintenance structures before the implementation of the Reliability stream, only critical elements should be changed or modified first. The business goal of Trimas Corp. was articulated in the Introduction and Background in Chapter 1 and needs no further discussion. The steps towards attaining reliability of the Paint Line are explained in the Asset Reliability stream, Figure 23.
4.9 Equipment Criticality ranking According to the Pareto Analysis, critical assets are the 20% of the total number of assets that produce or cater for 80% of the production. Identifying such assets is
59
most important as they are the ones that determine the very productivity, quality and after all the availability of product for sale. Critical assets are identified by a method of criticality ranking or simply Ranking Index for Maintenance Expenditures, RIME (Kister et al, 2006, Wikoff, 2012). In the case of the Paint Line, the most critical assets have been identified following their impact on these categories, Production volume, Safety, Quality, Maintenance and Environment as shown in the final scoring in Table 6.
4.9.1 Identification of Critical Assets a) Equipment criticality Equipment criticality ranking is shown in Table 3. Each piece of equipment is ranked based on the production process but with high regards on safety. It is important that production and maintenance leadership jointly assign equipment criticality as a team to avoid future confusion on job or work priorities. Table 3: The Equipment criticality table with weightings from 1-10 Criticality 10 9 8 7 6 5 4 3 2 1
Description Mission and customer impact Safety and environmental impact Shut down entire plant Shuts down more than one key production line Support equipment is not available Support equipment has been spared Infrequent use or planned utilised equipment Miscellaneous equipment, e.g. waste water pump Low probability of failure Low Asset replacement value
b) Human consequences The second ranking is based on the consequences of equipment on human beings as shown in Table 4. This involves occupational hazards and health of staff. The health of staff is equally important as productivity.
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Table 4: The human consequence table Ranking 8 7 6 5 4 3 2 1
Consequences to humans Multiple fatalities Single fatality Major injury, limb or sight loss Minor injury, days off sick Slight injury No injury Irritation or discomfort Poor lighting or housekeeping
c) Environmental consequences The third ranking is based on the effects of the equipment on the environment as in Table 5. Pollution can be devastating to humans and environment and in Australia this attracts heavy fines and litigation from Environmental Protection Agency (EPA). Table 5: Environmental effects Environmental consequences ranking 7 6 5 4 3 2 1
Description Massive effect (disaster) Major effect Local effect Minor effect Slight effect Potential effect No effect
4.9.2 Criticality Scoring results It is important to rank the plant equipment by impact of their failure consequences on production and safety as shown in Table 6.
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Table 6: Equipment criticality scoring for the Paint Line equipment Asset Conveyor chain and drive equipment Instrumentation and process control equipment E-Coat pretreatment system E-Coat weir and pumps system The Jindex and Filtration system Rectifiers, cathodes and anodes, anolytes and catholytes Powder coat section The Airless Shot Blaster Heat, ventilation and air condition equipment Drying and baking ovens
Environment Human Equipment Total factors Criticality score 1 6 10 17
3
3
9
15
3
4
8
15
4
3
6
13
5
3
7
15
1
7
8
16
3
2
6
11
3
6
8
17
5
2
6
13
5
4
7
16
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The use of equipment criticality ranking: 1) Enables maintenance engineering to scrutinize and collect data for decision making 2) Identifies the leading characteristic that makes the asset critical. 3) Through understanding the criticality ranking of any equipment a suitable maintenance management program can be developed. 4) Assets that are in the top 20% can be considered higher priority and Failure Modes and affect analysis (FMEA) be made to assess risk priority associated with each failure mode so that corrective action is taken before failure. 5) A combination of Asset Criticality ranking and Work Classification ranking produces the Ranking Index for maintenance expenditures (RIME). This is important as this number can be used to prioritize work by planners, schedulers and materials store management. The equipment criticality ranking, Table 6 showed that the conveyor and shot blaster were the most critical equipment. The e-coat electrical charging equipment comprising of rectifiers, cathodes and anolytes were ranked third together with the drying and bake ovens. This indicates that more effort and attention should be given to this equipment. 4.9.3 Data interpretation and impact assessment. The analysis concluded that there are three roots for failure which lie in the following categories: 1) People (Organisational structure, culture and climate) 2) Process and systems (Maintenance strategy). 3) Equipment (design, random failure) The Asset Reliability Stream, a solution used for mapping an optimal maintenance strategy was identified for structuring and implementation of a reliable and effective maintenance strategy and organisation. The data analysed on human resources indicates that there was lack of structured systems and processes to manage human resources. A new organisational structure
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was required to support maintenance and production. The areas to be improved include sizing of trade and supervisory staff in maintenance. In addition to that, the roles of reliability engineer, maintenance planner, maintenance coordinator and stores assistant would be introduced in the maintenance department. A process engineer would be added to the production team to ensure process systems and parameters are complied with. In summary, it is the absence of competent leadership and management coupled with lack of well-structured maintenance systems and processes that culminated in the increase of downtime, poor MTTR and MTBF. These ultimately affected the Overall Equipment efficiency.
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CHAPTER 5 RECOMMENDATIONS 5.1 Introduction Based on the analysis in Chapter 4 there is need for a consolidated approach to be implemented in order to achieve the objective of this research. Recommendations to the organisational structure, culture and climate change were given. Managing and leading people mattered most if work systems efficiencies were to be realised. The maintenance strategies to be implemented were drawn out. Different equipment would use methodologies suiting their operational characteristics and criticality. This meant drawing up a new maintenance schedule for preventive, condition based and turnarounds. Again different problem solving methodologies were identified for high risk and critical equipment. Recommendations on the procedure for daily start-ups were also identified together with the equipment. Items or equipment that must run on Operate to Fail were grouped in their own class. Lastly some trouble shooting recommendations on the e-coat system were given for the benefit of plant operators and production trade staff.
5.2 Changes to the organisational structure Figure 25 shows the current organisational structure. There are only four tradespersons including the maintenance supervisor with a maintenance coordinator vacancy that has never been filled. The whole maintenance team is led by the maintenance engineer and operates independently from other departments. For a change towards equipment reliability, a restructuring of the maintenance and production departments to fit a reliability based structure was required. This would mean some production personnel would be tasked with low risk maintenance work and at same time working together with Paint Line maintenance staff. They would form efficient self-empowered plant operating teams or SEPOTS, with the advantages that it promotes plant ownership and team working (Kelly, 2004).
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The current organisational Structure Group Managing director
Sales and Marketing Director
Product Engineering Director
Operations Director
Production manager()
Team Leader- Paint Line
Paint line staff
Maintenance Engineer
Team LeaderPreparation
Preparation staff
Qualit Manager
Maintenance suspervisor
Process quality techs x4
Maintenance fitter x3
Maintenance coordinator(vacant)
Figure 25 Current organisational structure. (Source: Trimas Corp.) With the SEPOTs structure in place, if the plant has broken down, everyone contributes to correct the failure, and when the plant is running maintenance revert to inspections, making spares, safety and extension projects, while production personnel, run the plant, monitor any anomalies and make inputs to process improvements. Besides this, these teams are given their own duties and make their own decisions. The Paint Line requires that Production own the asset and maintenance supports sustenance. In reference to the overall maintenance organisation of the company, the new administrative structure would be shown as in Figure 26.
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The proposed organisational structure
Group Managing Director
Sales and Marketing Director
Product Engineering Director
Operations manager
Maintenance manager
Production manager
Production supervisor (Paint line)
Reliability Engineer
Maint. Supervisor (Fabrication)
Maint. Supervisor (Workshop)
Night shift trades x2
Workshop trades - Rotables & Projects x3
Maintenance Planner
Stores& Material assist.
Maintenance coordinatorPaint line
2x trades +Operators- Day shift
Process & Quality engineerPaint Line
Process & quality technicians
2x trades +Operators Night shift
Day shift trades x2
Figure 26 Proposed operations organisational structure. (Source: Author) There are three very important aspects that will be discussed regarding the implementation of the new organisational structure. Some recommendations will also be given. These are the areas that affect the delivery of maintenance and they are organisational culture, climate and training and development. a) Organisational culture Since the Trimas organisation structure would have changed, the culture would need to change also. Certain negative behaviours and traits could have been exhibited in the previous regime. It is the duty of management to instil a sense of new culture that will embrace action and attitudes towards
67
reliability. The maintenance and production would be committed to support production by efficiently maintaining and operating as SEPOTs. Trimas management would train them to form such teams. A sense of goodwill and motivation from Group Managing Director to floor supervisors in Paint Line should be instilled. b) Organisational climate Organisational climate is the prerogative of management at Trimas. They have to be responsible for pre-setting the right working environment. The style of leadership and ability to harness and listen to all employees can make change possible towards best maintenance practices, productivity, low stress levels, absenteeism and employee retention, It is recommended that supervisors and managers at the Paint Line undergo training and development at the same time as floor workers are trained on the equipment and new business approach. c) Training and development This element is necessary especially when there is a change going on. The survey on Table 2 indicated that Trimas maintenance trade staff and operators and supervisors lacked in understanding of new technology such as PLCs, CMMS and basic cross skilling. Those who lack these skills should be identified and be trained. The training budget is a requirement in maintenance regimes and is rated at 4% of the payroll. (Mitchell, 2006) 5.3 Re-designs and developments to Paint Line equipment Through interviews and interaction with personnel working on the Paint Line it was noted that in order to improve the reliability of the asset some changes or modifications were to be made. Modifications were identified as a priority project for the purposes of quickly arresting recurring Paint Line track problems caused by structural deformities. This project would run concurrently with the rest of the steps in the Asset Reliability stream. The re-designs and modifications were summarised below as follows: 1) The Paint Line track required installation of power chain shot cleaning station and automated lube stations as shown in Figure 27.
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2) The Paint Line structural framework needed stiffening or strengthening. It also required an increase in the U-turn radius and alignment of the track to ensure smooth cornering as in shown in Figure 28. 3) Long power chains were to be replaced by multiple short single units power chains that would include installation of fail-safe monitors, load monitors, gear motor with electromagnetic clutches or mechanical overload torque protectors. 4) Power chain inspection points for human eye inspection or by video camera should be installed.
Figure 27: Brushes installed for cleaning the power chain. 5) Installation of conveyor maintenance lanes and faulty trolley removal ports. 6) Changing of E-coat and Pre- treatment wash booth pipes from PVC (plastic) pipes to stainless steel pipes. 7) Modification to enhance efficiency of Exit stoppers, mergers and diverters on conveyor to avoid jamming and improper operation. 8) Installation of spare UF and RO water pumps and pre-treatment pumps to increase reliability of system in case of failure of one pump.
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9) Installation of Induced draught fan to remove waste gases from all ovens for safety and environment.
Paint Line Steel tubes reinforcing the Paint Line
Figure 28: Frameworks to strengthen the framework of the Paint Line 10) Installation of tougher vestibule seal on the Airless shot blaster, and enclosing the shot blaster room and also installing an overall dust exhaust fan. 11) Installation of safety platform around the shot blaster to enable safe inspections and maintenance work.
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5.4 Implementation of the Paint Line reliability care plan This section looks at ways of optimising reliability and availability of the Paint Line through different maintenance methodologies. 5.4.1 Introduction In the problem definition, the failure modes and their effect to the asset where identified. The failures happened on different parts of the Line. Some were minor others major and also recurring, even catastrophic. Some required simple corrective actions, others overhaul, replacements or design-outs. Minutes, hours and days were spent to correct failures without assurance that this will not happen in the future. These statistics prompts the view that there should be different maintenance strategies to lift the uptime and reliability of the plant. Paint Line Availability Log sheets on appendices A to C will be referred to. From the log sheets it can be seen that not only is the chain breaking up but the Shot Blaster, E-coat circulation pumps, and faulty divert stoppers and electrical rectifiers were also major contributors to downtime. Besides all these, process parameters like poor rinsing, faulty filtration and incorrect ph. values of the paint were also causes for concern, and they caused low product quality and output. Figure 29 shows the results of a faulty pump and poor circulation. This can cause frothing and poor paint mixture leading to low paint quality. To attain a high reliability rate the use of Reliability based maintenance strategy cannot be understated. Thus in this chapter sections of the Paint Line that require their own strategy will be categorized to suit their maintenance methodology amongst them, Preventive, Operate to fail, Predictive/Condition based, or design-out maintenance or a combination of methodologies. Most of the Paint Line failure modes have been identified in the Problem formulation section, Chapter 2 that described the problem. It is now important to put in place a Reliability care plan to increase total plant assurance and availability of the Paint Line.
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Figure 29 E- coat pump leaking (left) and the rinse system frothing (right).
5.4.2 Application of problem solving methodologies to the Paint Line Problem solving methodologies are essential on the Paint Line for rooting out the origins of equipment failures and estimating the rate or occurrence of problems. Table 7 shows the recommended problem solving methodologies, the area of application and the responsible persons for the task.
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Table 7: Application of problem solving methodologies Methodology RCA
Area of application E-coat process, pumps, conveyor chain drives, Rotables and simple equipment
FMECA
Basic mechanical, electrical and electronic equipment and process issues. All mechanical, electrical and instrumentation equipment Productivity and quality issues. All mechanical, electrical and instrumentation equipment, Productivity and quality issues
Fault Tree Analysis
Responsibility All maintenance personnel & supervisors. Management responsible for implementation of solutions Maintenance manager, Reliability engineer, technician, Planner
Maintenance and Reliability engineer Maintenance manager
5.4.3 Improvements on Total Productive Maintenance By definition, it is a manufacturing led initiative that leads to effectiveness of manufacturing equipment and is done to prevent breakdowns cost effectively. In other words it is a team based productive maintenance involving executives to shop floor. This candidate recommends formulation of a comprehensive yearly PM schedule for subsections of the Paint Line. The Line would be divided into sections, which are the Shot Blaster, Pre-treatment and E-coat section process equipment, and the Powder coat ovens equipment. The Conveyor chain’s PM would be divided into the number of drives with a given asset no as Drive Motor No 1 to 15 etc. Additional PM schedules should be done for electrical and instrumentation equipment.
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5.4.4 Daily inspections and start up A daily inspection program for both maintenance and production team (SEPOTs) is essential to correct and set up equipment before start –up. Daily inspection sheets should be completed by SEPOTs and then sent to the Reliability engineer, maintenance planner, all supervisors and Maintenance manager for analysis through the CMMS. A general plant assessment and healthy chart can then be made. Through this, corrective actions can then be planned and scheduled. TPM and Daily inspections enable trade and operations staff to quickly know their plant, its condition, variations and performance rate. It increases the overall equipment efficiency which is approximated at 85% as stated by Kister et al (2006). Mitchell (2012) also supported this strategy and approximated that this would increase plant availability to at least 97%.
5.4.5 Predictive maintenance/ Condition monitoring It is not possible to reach the suggested figure of 97% indicated by Mitchell in Maintenance benchmarking without considering stoppage times during inspections, line set-up and PMs. Stoppages consume production time, thus to increase up time and avoid unnecessary downtime incurred during maintenance outages, condition monitoring technologies can be harnessed to monitor critical parts or sub-systems of the Paint Line effectively. The Paint Line currently uses a central monitoring system called the FAT control to check out the conveyor drives torque, motor speeds, current, and process pump pressures. It has been noted that the FAT control does not monitor the condition, pattern of deterioration to point of failure as shown in the pdf and Bath tub graph shown in Figures 21 and 22 respectively. It just indicates the status of equipment, whether it is running or stopped. Although costly, condition monitoring is unavoidable in this risk and competitive business world. Its advantages have already been stated earlier in the Maintenance Frameworks, sub- section 3.7. It is recommended as in Table 8 that the following parameters or parts of the Paint Line be monitored by suitable gadgets or instruments.
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Table 8: The equipment to be monitored by predictive technology No
Equipment
1
Shot Blaster: gearboxes
2
Shot Blaster: Electrical Motor current tests, motors vibration analysis
3
4
5
6
7 8 9
Diagnostic techniques/ Method
Frequency
All Oil sample analysis and vibration Fortnightly analysis Vibration analysis Weekly
Paint Line chain drive Motor current tests, motors vibration analysis Paint Line: All chains Lube analysis, & sprockets spectrographic & ferrographic analysis Pre-Treatment pumps & Vibration analysis, motors laser alignment Drying and bake ovens Vibration analysis, lube analysis blowers
Monthly Quarterly Monthly Every 2 months Monthly Quarterly Monthly Monthly Monthly
Tanks and piping
Metal fatigue, corrosion tests, acoustic Half yearly emission, sedimentation Electrical starters, Time/ resistance tests, thermal imaging, Yearly cables, transformers infra-red scan, ultrasound, oil analysis Shot blaster, E-coat Air quality index tests Half yearly ovens & Powder coat booth
It must be noted that specialists in the field of condition monitoring should be engaged and work with a selected and dedicated team from both maintenance and production in order to realize the full benefits. Vibration monitoring is the most common of the condition monitoring techniques as there is more rotating machinery than any other category. An example of recommended limits for vibration velocity can be extracted from the Australian Standards, AS 2625 or ISO 10816 that shows Vibration severity level and Alert chart for machines.
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5.4.6 Operate to Fail (OTF) Operate to failure is also a maintenance strategy. It is most suitable for low risk assets that can be found on the Paint Line. Such assets would have readily available spares, cost less to replace and would not affect quality or productivity of the main stream production process. Furthermore equipment run on this philosophy are anticipated not to put any pressure on maintenance personnel when repairing these types of plant items. Thus it would be appropriate to run such equipment until it fails. 5.4.6.1 OTF application areas Some of the identified equipment on the Paint Line that can fall in this category are as follows: waste water agitators and pumps and E-coat bag filters, chain tension air cylinders, powder coat air cylinders and purging valves, shot blaster purge valves, shot blaster feed valves, vestibule seals and brushes. Figure 19 shows how maintenance strategists can determine how an asset can be categorized into different maintenance tasks or frameworks. Although a few insignificant items fall in OTF, caution must be taken to periodically assess each individual situation since costs of equipment replacement, labour and time all have an impact on life cycle costs as situations, conditions or modifications demand. In view of this, overtime, downtime and inventory can accrue unnoticed when these “insignificant” assets are being maintained. It is important to keep every document related to maintenance like maintenance history and related costs in order to identify abnormalities.
5.4.7 Shutdown/Turnaround Maintenance It is recommended that shutdown maintenance work be executed for the purpose of plant items refurbishments, replacement, or expansion. This task is given to the Maintenance planner, Reliability engineer and all programs and tasks would need to be approved by the Maintenance manager and top management.
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5.4.7.1 Turnaround scope This strategy would seek to correct recurring failures or inefficient systems and improve reliability and therefore increase productivity. Windows of opportunity for shutdowns are available during the end of the year where there is a period of 2 weeks before year-end. Other days that can be scheduled for maintenance are the monthly Roistered Day Off and on weekends. These two periods are suitable for low workloads because of limited time. The work scope identified for shutdown includes the following: a) Chain conveyor: All conveyor chain sections to be completely replaced or pulled-off inspected, replacing damaged links and trolleys. Inspection, repair or replacement of caterpillar chains and sprockets including drive motors and gearboxes. Inspection and replacement of both power and free tracks for damage and structural deformities. Inspection and replacement of diverters, mergers, control solenoids and proximity switches. Repair of lubrication lines. b) Shot blaster Replacing of blasting chamber plates, dampers and curtains Replacement of vestibule seals and brushes, Inspection of bucket elevator system, all screw conveyors and shot strainer. Inspect and replace shot gate valves, and blaster wheels. Inspection and repair of shot blaster dust extractor. Conduct motor current tests on all electric motors and control instrumentation. c) E-coat and drying ovens Cleaning and inspection of all wash water and rinse tanks, and pipework. Inspection of all pumps, valves for efficient liquid delivery.
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Cleaning of e-coat tank and rinse pipework. Inspection and testing of e-coat bus bars. Inspection of drying ovens and exhaust flue paths.
5.5 The Computerized Maintenance Management System or CMMS Reliability, organisational efficiency and effectiveness can be difficult to achieve if the maintenance information flow is not set up well. The CMMS is a power tool for inter-departmental communication, production, finance, sales, marketing and others. It is the duty of the maintenance planner to run the CMMS program assisted by the Reliability Engineer. Besides these two, the maintenance supervisors should be able to assist the maintenance planner through daily inputs of their on-going work schedules, job reports and other needs. The CMMS keeps the PM schedule, asset inventory, maintenance history, inspection records and Condition monitoring data. In addition to that, records of spares, tracking of work done and lists of job orders are all recorded in this program. Besides these the CMMS keeps the records of time spent on jobs, planned and scheduled work, contractor history and their costs. As a management tool it can be used to assess some of the critical KPIs to ensure best maintenance practices are attained as stated below: 1) Availability of plant/ asset which is rated at plus 97% 2) Reliability of Equipment/Mean time between failures which is supposed to increase at 10% per year if equipment maintenance is effective. 3) Individual tradesperson performance- usually measured by wrench time and meantime to repair rates. 4) Whole plant utilization rate. 5) Total maintenance costs /total Manufacturing costs, rated at less than 15% 6) Budget compliance, 7) Unplanned downtime at 0% 8) Planned maintenance / total maintenance rated at plus 85% 9) Maintenance cost / Replacement asset value of plant & equipment, less than 3% 10) Monthly maintenance strategies benchmarks.
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a. b. c. d. e.
Reactive emergency hours/ Total maintenance hours, rated at 2% Predictive maintenance hours/ Total maintenance hours rated at 50% Preventive maintenance hours/ Total maintenance hours rated at 20% Planned reactive maintenance hours/ total maintenance hours at 20% Reactive non- emergency hours to Total maintenance hours at 8%
11) Vendor management and inventory turns. 12) Maintenance reports. 13) Contractors cost to Total Maintenance cost, rated at 35-64% Furthermore the CMMS’s advantage is that it can be used for Quality management or TQM, ISO 9000 purposes. Through the CMMS the Reliability Engineer, maintenance planner and supervisors can identify equipment problems, initiate continuous improvement plans by isolation and solving them to prevent further occurrence. Thus the entire maintenance organisation would be required to use the PIE-C method, a process shown in Figure 24 to implement these changes and evaluate success. As a quality control tool, PIE-C aims at improving the reliability of individual plant item through planning and identification of critical components of a system or parts of equipment. The second stage aims at identifying what needs to be improved or done. Stage 3 is the implementation stage of the corrective measures. The last stage is the evaluation and control stage which is used to steer the process to achieve the desired goal.
5.6 Spares Management In the quest to attain reliability and availability it is necessary that spares and rotables management is regarded as key component of the maintenance organisation. An optimum amount of spares should be kept in order to support the needs of the maintenance department. It is the responsibility of the maintenance planner and the stores assistant to order, receive and store up spares to avoid work delays and stoppages. The following was recommended for the proper management of spares for the Paint Line.
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5.6.1 Inventory policy An inventory policy for fast moving and slow moving parts was recommended as there was none in place. The re- order level and re-order cycle type of method could be used for fast moving spares as shown in Table 9 and Table 10 as an example. Table 9: Fast moving spares Re-order levelreplenishment prompted by reduced stock or alarm level Re-order cycle-replenishment by decision or by calendar
Chain trolleys, chains, Load bar contact strips, trolley bearings, load bar bolts and nuts, wash spray nozzles Load bars, chain lubricants, e-coat gland packing seals, Jindex strainer membranes, Conveyor tube segments
Table 10: Slow moving spares. Random failure partsinfrequently but randomly Wear-out failure parts
occur Caterpillar chains and sprockets, Takeup units, electric motors, draught fans, pumps, switch gears, fuses , Shot blaster wheels, shot blaster wear plates, conveyor tube segments, control sensors, e-coat bus bars, shot blaster seals and brushes, gearboxes
The spares identified as slow moving are those that would be more expensive in value and overshadow fast moving spares. Table 10 shows Paint Line items considered as slow moving. These items are rarely noticed quickly enough to enable correction but their purchase value and holding costs increase their overall cost.
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5.6.2 Rotables Rotables are parts or plant equipment that can be reconditioned in the local workshop or outside by contracted organisations or original equipment manufacturers, (OEM).
Trolleys and dry bearings to be reconditioned locally
Figure 30 Conveyor chain trolleys and bearings to be reconditioned.
It is recommended that equipment suitable for reconditioning is given stores code, or number and be recorded in the stores system and in the CMMS. This would enable tracing of costs and location during its circulation in the rotables system. An example of rotables location is shown in Table 11. Some critical rotables are shown in the Figure 29.and 30.
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Table 11: Allocation of rotables Rotables – Trimas workshop
Load bars, conveyor trolleys, take-up pneumatic cylinders, Electric motors, gearboxes, fans
Rotables- Contractors, OEM
5.6.3 Use of the CMMS in spares management The planner should draft an inventory of all possible parts and their individual costs, stock number, vendor and location in the stores into the CMMS. The parts should also relate to the name of the asset the uses it. A re-order level should be established for quick moving items.
Figure 31 Critical conveyor parts held as spares
5.7 The E- Coat Process: Troubleshooting recommendations In order to increase the protective and decorative finish, common defects should be eliminated in the e-coat process. E- Coat troubleshooting is similar to the Root cause analysis. The process that could be used to mitigate equipment problems and quality of product in the e-coat system were as follows,
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1) E- Coat troubleshooting process, 2) Establishing preventive maintenance schedule, 3) Controlling operating parameters and classifying e-coat defects as found by Trimas quality department. 5.7.1 E-coat troubleshooting process A sound workable process should be used to solve e-coat problems. A problem in the e-coat system should be characterized by answering these questions in these categories. Isolation- is problem in the e-coat system or product appearance Defect- what type of defect, is it appearing in all products Location-is it occurring at a particular part of the product or system Time- when did the problem start Duration- is it constant or sporadic After this it is necessary to find the root cause of the problems by figuring out and correlating these types of defects to the following, 1) 2) 3) 4) 5)
E-coat tank variations. RO and UF filtration problems. A probable change of drying and baking parameters. Inadequate electrical discharge by the discharge strip. Other parameters related to electrical and mechanical equipment that affect the quality. This problem solving procedure should be followed up by determining corrective action, implementing corrective action and following up the results to avoid re-occurrence. It has been noted that most problems emanate from defective equipment. 5.7.2 E-coat system preventive measures Preventive action is a guard against failures in the e- coat system. The use of advanced technologies to monitor changes or compliance in the operating parameters of the e-coat is most advantageous. It reduces product losses and unseen catastrophic failures before they occur. Considered in this set of
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recommendation are mechanical, chemical and substrate systems that require preventive maintenance. Tanks and pumps- Proper tank agitation is necessary for paint suspension, filtration, and heat removal generated by pumping and coating. Broken or misaligned eductor and headers affect pump circulation and agitation. A malfunctioning pump causes foaming appearance defects of the product and also poor bath circulation. Half year cleaning periods must be done for the tanks and weekly cleaning of filters done in the Jindex or when pressure drops below the required threshold Drying and baking ovens- Oven air circulation should be checked semiannually and the pyrometers tested to ensure proper operation and readings. Rectifiers- The rectifiers should be checked half yearly for ripple, and should not exceed 5% under stated load. The amperage and voltage display should be calibrated every 4 months to ensure accuracy. As a safety measure no voltage should be active if there is no production. Electrodes should be checked for degradation; proper supplies of energy levels weekly and ensure electric cables are connected securely. Periodic check of anode amperage is needed to monitor anode performance and the 2 minute immersion period should be maintained. Anolyte/ catholytes- Pumps circulating this liquid should be checked and their instrumentation checked. The conductivity indicator and probe is to be monitored to ensure removal of excess acid and base from paint bath. Filtration and rinsing- Paint tank filtration is done through filter bags and ultra-filters. Bag filters should be changed when pressure differential between outlet and inlet is 5psi. Ultra filter flux rate should be checked using pressure gauges installed on the system. Rinsing- Misdirected missing and broken nozzles must be checked for effective operation. Rinse flow must be balance stage by stage. Settled paint solids and fallen parts should be removed. Piping pressure is to be maintained in the piping system at 5-10psi Cleaning process- Proper cleaning methods are required to ensure good quality finish. Substrate contaminates like descaling shot, dirty surface,
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stamping oils, fibres and weld smut affect adhesion film. Thus the cleaning alkaline, circulation pumps and aeration pumps must be efficient Water quality- Water with low conductivity and microbes and low silica levels is recommended. A set time for cleaning resin beds and their regeneration is needed. 5.7.3 Parameter effecting on quality It is important that Paint Line staff understand the impact of equipment health on process parameters. Furthermore, it is important that they also know and understand the effects and causes of these parameters to the quality of the product. The list below was drafted to show the effects of certain parameters to the quality of the finish. Most of the problems in this section point out to pump and filter inefficiency, inaccurate process instrumentation and measurement equipment. Once the parameters are below the required levels, the product quality deteriorates. In such situations, re- works are not permissible. The most common problems are as follows: 1) Bath solids- This includes the pigments and other paint components. They affect low film thickness, higher rupture voltage and ultra-filtrate flux rate. This is caused by over replenishment of paint paste. 2) Bath ph. - High bath ph. is caused by caustic contamination or excessive caustic addition in deionized water. It causes tank settling, dirt and lowered ultrafiltration rates. Low ph. is caused by too much acid and can cause dissolution. The other causes are clogged ultra-filtrate membranes. 3) Bath conductivity- High bath conductivity cause rupturing, high film build up and roughness. High bath conductivity is caused by poor pump filtration and poorly deionized water. Low conductivity is caused by excessive ultrafilter purging and low bath solids. 5.7.4 Common electrocoating defects The most common defects caused by malfunctioning of equipment are listed in Table 12. It is the responsibility of the Paint Line leadership to train the staff to identify these problems and also implement corrective measures.
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Table 12: How equipment problems cause product defects. Defect
Equipment problem
Cratering
Inadequate filtration of paint, rinses and substrates and water, chain oil or grease contamination. It can be caused by anodic heat generations and electrical cathodic sparking or gassing on the product because of excessive voltage. It is caused by ionic contamination, poor filtration of solvents and substrates. This is caused by excessive solubilizer, high solvent levels and Conveyor stoppages. Dirty on the product is caused by inadequate solubilizer levels, pump shearing, improper circulation and filtration. Is caused by pump cavitation and poor tank circulation and inhibiting gas or air escape. Is caused by low voltage, low bath solids, low conductivity, high solvent levels and insufficient deposit time. Is caused by cure time and temperature variations, improper agitation, solubilizer levels, pigment to binder ratio. This is caused by low contact, faulty rectifiers, inadequate electrode surface, low voltage, and inadequate bath temperature and deposit time.
Rupturing Roughness Redissolution Dirt Foaming Throwing power Gloss variations Thin coating
It is the primary duty of the production operators and supervisors to keep track of these parameters. It is common in a process environment to have problems that replicate after one parameter is out of its boundaries. The effect can be two fold, either on the equipment or product. It is the responsibility of the process engineer or production supervisor to draft plant SOPs and also corrective procedure to arrest such problems.
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CHAPTER 6 CONCLUSION This thesis highlights the problematic state of the Paint Line. In order to overcome the problems some recommendations have been made. The recommendations were based on the author’s own work experience on similar equipment and industries elsewhere. An Overall Equipment Efficiency (OEE) of up to 85% can be achieved when these recommendations are implemented. The Paint Line problems were described according to each section, i.e. Airless shot blaster, E- coat section, Paint Line Conveyor, and the Drying and baking ovens. Its overall performance was also analysed. The financial impact behind the loss in Reliability and Availability of this asset was calculated. The hourly loss of $55 000 per 12 hour shift was revealed. The data used for analysis in this thesis was collected from job requests forms, quality performance sheets, process parameter sheets and the Paint Line Availability Log sheets. Problem solving methods such as RCA, FTA, Fishikawa, FMECA and Condition Monitoring were identified as suitable reliability tools for equipment failures analysis. The Non Destructive Testing method (NDT) was also recommended as part of Condition Monitoring for specific components. The maintenance strategies that are applied in different types of industries were examined in the current context and some of them resonated well with the business objectives of Trimas Corporation. The traditional preventive maintenance (PM) is still being practiced worldwide while Operate to Failure (OTF) was recommended as a cost effective strategy for certain equipment on the Paint Line. It was noted that to attain reliability, the RCM strategy guided by the business centred approach needs to be developed, The Asset Reliability stream was identified as a suitable method to map out the new maintenance structure, strategies and systems. It would be complimented by the PIE-C method that ensures proper implementation and evaluation of each stage of the Asset Reliability stream. The Paint Line equipment was assessed using a criticality ranking index before recommendations were made. The Conveyor chain was ranked first, with the E-
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coat treatment section coming second. The recommendations were made and they varied from implementation of preventive maintenance program, re-designs and development, implementing a Predictive strategy to certain equipment and recommended trouble shooting process of the E-coat system. Furthermore the organisational structure to fit the maintenance strategy and objective was established. It was identified that there was lack of a work management system which is critical in ensuring smooth flow of work processes and information management. It was recommended that MEX CMMS be fully utilized and training for its use be conducted. This system is important for interdepartmental communication, planning and scheduling, storing information and also for spares management. Lastly, the human factor in attaining reliability is important. Lack of skills and technical knowledge of the Paint Line proved retrogressive, thus training and development was required to improve staff performance. The analysis in this thesis was based on the data available. Since there were problems in collecting data from different departments, thus the quality of the data is based on what was available and is agreeably not of high quality. Continuous improvement of the Paint Line is required over a period to achieve maintenance excellence. It helps raising the bar as it sustains the incremental gains in equipment performance whilst reinforcing the new work process effectiveness. An effective and efficient human effort in a good working environment would also be required to compliment the improvement. Lastly it is the management principles that govern organisational behaviours in both maintenance and production. Thus management should be able to articulate the organisation’s vision and values and create a high performance culture coupled with job satisfaction.
Areas of future research There are some areas in this research of Reliability and Availability that would need future or further study. These are as follows:
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1) The effect of the strength of materials and supporting frameworks of assets offering firm structures and ultimately high reliability rates during operation is a point of concern. This issue has been prompted by the analysis of the Paint Line structure and its subsequent modifications. 2) The introduction of operator maintainer staff, team based maintenance tradesmen and the viability of predictive technology to increase reliability and availability in the near future. Computers and modern gadgetry in maintenance management are no longer fears but necessities. 3) There is need to study the effect of the cost of production and maintenance whilst aiming for Reliability and Availability in a future Green manufacturing environment. This has been prompted by rising energy prices through the introduction of the Carbon Tax scheme for the reduction of emissions (Hepworth, 2012)
4) The uses of mathematical probability methods to predict failure of components or systems is still a topic that needs to be applied throughout maintenance. It is still difficult to be embraced by non-engineering people. It is hoped that such methods will be simplified by use of computer software and technology and will become suitable for use by maintenance craft with basic mathematical aptitude.
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Appendix
A-
Paint
Line
Daily
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Availability
Log
sheet
Appendix B- Paint Line Daily Availability Log sheet 2
95
Appendix C- Paint Line Daily Availability sheet 3
96
Appendix -Coat and Pre-treatment performance log sheet
97
Appendix E- Garnic Technologies (OEM) failures log sheet
98
