Innovative Quality Management System for Flexible Manufacturing Systems T. Bihi, N. Luwes, K. Kusakana Department of Electrical, Electronic and Computer Engineering Central University of Technology Bloemfontein, South Africa Email:
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electronics; with the transistor and microprocessor, but also the rise of telecommunications and computers.
Abstract— The next generation of industry; Industry 4.0, holds the promise of increased flexibility in manufacturing, along with mass customization, better quality and improved productivity. In the Industry 4.0 era, manufacturing systems are able to monitor physical processes and make smart decisions through real-time communication and cooperation with humans, machines, sensors, and so forth. Intelligent manufacturing is based on this concept of optimizing manufacturing by taking advantage of technological advances. Flexible manufacturing systems are a form of intelligent manufacturing. A Flexible Manufacturing System reacts to changes in the production process, this includes changes in the product and the production schedule. The problem is that a traditional Quality Management System cannot be used for a Flexible Manufacturing Systems because it cannot keep up with the changes in the FMS. The aim of the project is to design, construct and evaluate an Intelligent Quality Management System (QMS) which can learn, and adapt to the change of the flexible manufacturing system (FMS). It will be able to do this by designing hardware nodes that can be easily added to already implemented test systems that convey information back to an Intelligent Quality Management System that would learn the line lay out and setup with predefined training cycles. Thereafter it should run as a Quality Management System until the flexible system necessitates a retrain. Keywords— Flexible Manufacturing Manufacturing, Quality Management.
I.
System,
Figure 1: Four Major Revolutions of Manufacturing
Industry 4.0 is a name for the current trend of automation and data exchange in manufacturing technologies. It includes cyber-physical systems, the Internet of things, cloud computing and cognitive computing. Industry 4.0 is commonly referred to as the fourth industrial revolution. Subsections of industry 4.0 is flexible manufacturing systems and quality management [2].
Intelligent
A flexible manufacturing system (FMS) can be defined as a computer controlled production system capable of processing a variety of part types. Flexibility characterizes production ability to be readjusted to the multipart, small or medium-batch production. There are various flexible manufacturing systems categorized according to the targeted process being improved. These categories are as follows [3, 4, 5]:
INTRODUCTION
The manufacturing industry is the basis of a nation’s economy and powerfully influences people’s livelihood. Emerging technologies can have a major impact on manufacturing models, approaches, concepts and even businesses [1].
1. Variant flexibility: Ability to manufacture or assemble more variants of a product. (Product flexibility)
Manufacturing went through four main revolutions. The first revolution spans from the end of the 18th century to the beginning of the 19th century and involved the emergence of mechanization. Nearly a century later the second revolution was sparked when new technological advancements initiated the emergence of a new source of energy: electricity, gas and oil. As a result, the development of the combustion engine set out to use these new resources to their full potential. A third industrial revolution appeared with the emergence of a new type of energy whose potential surpassed its predecessors: nuclear energy. This revolution witnessed the rise of
2. Quantity flexibility: Ability to adapt the production system to fluctuating volumes. 3. Technology flexibility: the ability of manufacturing and assembly system to be used for a number of technologies. 4. Successor flexibility: ability to use equipment or parts also for future products.
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5. External flexibility: ability to change the system by exchanging elements (example replacing robot gripper).
of such systems necessitates control based on good data management [18].
6. Internal flexibility: ability to change system without modifications (example automatic tool change).
Regarded as the main contributors to various environmental problems, firms are facing tremendous pressure from the government, consumers, media, environmental nongovernment organizations and other stakeholders to incorporate both quality management and environmental management into their business practice [19].
7. Personnel deployment flexibility: ability to operate with more or fewer employees and with different qualifications. This intelligent manufacturing takes advantage of advanced information and manufacturing technologies to achieve flexible, smart, and reconfigurable manufacturing processes in order to address a dynamic and global market [6]. It is regarded as a new manufacturing model based on intelligent science and technology that greatly upgrades the design, production, management and integration of the whole life cycle of a typical product [7]. Production efficiency, product quality and service level will be improved [8].
The need for more flexible and efficient data management in manufacturing systems has become obvious. To secure the highest utilization rate and maximum productivity of manufacturing systems it is necessary to be able to find the right information at the right time and at the right place; Just in Time. Non-production and inefficiency in single operated, stand-alone NC-machine tools and other NC-equipment are due largely to humanly caused elapsed times between the receipt of information, the formulation of a decision and the performance of the command [20].
Flexible manufacturing consists of concepts like Intelligent manufacturing, cloud manufacturing and IoT-enabled manufacturing [2]. There are similarities when looking at the aims of intelligent/smart decision-making in manufacturing systems and the optimization of various manufacturing resources [9].
A typical automation system would be tasked with assembling and verifying the assembly of that product. This would involve certain data being processed by the system like the digital and analogue data retrieved from proximity and other sensors. Image data from the quality inspection performed by the machine vision station(s), as well as prompts and messages send back and forth between the different stations, the assembly management Information Technology system and the database system responsible for archiving any of the data designated to be logged for future use [21].
In the Industry 4.0 era, an Intelligent Manufacturing System (IMS) uses service-oriented architecture (SOA) via the Internet to provide collaborative, customizable, flexible, and reconfigurable services to end-users, thus enabling a highly integrated human-machine manufacturing system [10]. This high integration of human-machine cooperation aims to establish an ecosystem of the various manufacturing elements involved in IMS so that organizational, managerial, and technical levels can be seamlessly combined. An example of IMS is the Festo Didactic cyber-physical factory, which offers technical training and qualification to large vendors, universities, and schools as part of the German Government’s Platform Industry 4.0 strategic initiative [11].
Operational control of an FMS is very complicated and involves accessing large static and dynamic data sets; representing machine configuration and characteristics, system status and process plans and complex control algorithms. The control algorithms are structured hierarchically, where an upper level issues commands to a lower level and obtains feedback on the achievement of these commands [22].
The flexibility of these systems is limited only by their parameter of geometry, power and function, though within these constraints they can perform an almost infinite variety of tasks [12, 13]. Flexibility allows the adjustment of the manufacturing system within a defined flexibility corridor [14]. In this sense, flexibility describes the ability of a production system to adjust the manufacturing system very quickly and with little cost. Changes are defined through predefined packages of measures and are limited by certain flexibility corridors at the time of planning [15].
II. INTERFACING THE FMS AND QMS To construct an Intelligent Quality Management System for Flexible Manufacturing Systems sensors needs to be connected from the Flexible Manufacturing Systems to the Quality Management System. There are a number of different means of integrating the information provided by multiple sensors into the operation of a system. The most straightforward approach is to let the information from each sensor serve as a separate input to the system controller [23, 24]. This mentioned approach of treating each sensor as an individual input to the system controller is exactly the kind of logic that will be employed to manage the communication and data exchange between the FMS and the QMS under development.
A Quality Management System (QMS) is a set of policies, processes and procedures required for an organization to meet its objectives and continually improve its capabilities [16]. Product and environmental quality are critical to the welfare of human beings. Recent research on QM in the international Journal of Production Economics has been connected to many other domains such as impact on innovation, company performance and corporate social responsibility [17].
To connect sensors to the Quality Management System one must consider hardware interfaces. Arduino is an open-source electronics platform based on easy-to-use hardware and software. A microcontroller consists of a microchip on a circuit board with read-write capabilities, memory, inputs and outputs [25].
Mixture data management together with tool management forms an important unit in FMS. Both tools and fixtures have a great effect on product quality. This is especially important in FMSs because of the high quality requirements. Unmanned use
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Arduino boards are able to read inputs; light on a sensor, a finger on a button and turn it into an output; activating a motor, turning on an LED, publishing something online. You can tell your board what to do by sending a set of instructions to the microcontroller on the board. In order to do so you use the Arduino programming language; based on wiring and the Arduino Software (IDE); based on processing. Arduino has been used in thousands of different projects and applications, the Arduino software is easy-to-use for beginners, yet flexible enough for advanced users. Arduino also simplifies the process of working with microcontrollers, but it offers some advantages over other systems. The two advantages that stand out for the purpose of the proposed production information system are the cross-platform application of the Arduino, as well as the simple and clear programming environment [26]. III.
PROBLEM WITH CURRENT QUALITY MANAGEMENT
Figure 2: Different Arrangements of A FMS
SYSTEMS
IV.
Flexible manufacturing facilities like traditional manufacturing facilities need to be able to provide product information sheets. Flexible manufacturing is different to traditional in the main aspect that the manufacturing system is designed to adapt to changes in product and product quantities.
PROPOSED INNOVATIVE QUALITY MANAGEMENT SYSTEM
A. Aim and objectives The aim of the project is to design, construct and evaluate an Intelligent Quality Management System (QMS), which can adapt to the change of the flexible manufacturing system (FMS). The design and construction is of an easily initialized system requiring no advance programming when the flexible manufacturing system is rearranged or replaced with another. The QMS interface would include hardware nodes setup to detect which inputs and/or outputs are being used by the FMS and also if those inputs and outputs (IO) are configured for analogue or digital signals. These IO will be wired into the different cells and even after a change in the arrangement there would still be no need for any loss of time or reprogramming of the QMS.
The problem in Flexible manufacturing can be explained with the following case study that encompasses a flexible system tasked with the assembly of circuit breakers. Assume that all tests are done on the same line as seen in arrangement 1 below. Then the arrangement needs to change for any reason to either 2 or 3. The need for Intelligent Quality Management System arises in arrangement 1 to log the data of the circuit breakers while at the same time automatically detecting if it qualifies as a pass at the 5 amperes, 10 amperes or 20 amperes electrical test. The test defines the type of circuit breaker that is under assembly.
Initially the QMS needs data to learn. This could be done by sending known samples with corresponding QR codes down the line. With this the intelligent system would learn which hardware nodes correspond to the relevant product and what the hardware inputs should translate. This will be done in programming mode. Provide enough data to the QMS with specifics of the product, in all the possible variations of it. In run mode products would be send down the line and evaluated and logged with the newly learned methods. The order of the cells will be determined and the hardware nodes will be scanned. The scan determines which of the IO are in use. A reconfiguration or rearrangement of the FMS cells will necessitate a quick adjustment to the QMS. This would require the QMS being put into program mode and product sample data fed in so that it learns about the product, and also the order of the cells as they interact with the product.
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B. Methodology and Research design The main aim of the project is to design, construct and evaluate an Intelligent Quality Management System (QMS) which can adapt to the change of the Flexible Manufacturing System (FMS). Design and construction in the pursuit of this aim is divided into hardware and software parts. Hardware includes the FMS and hardware nodes that are part of the interface to the QMS. Software on the other hand has to do with the QMS; the procedure of determining the order of the cells/ stations, scanning through the hardware nodes and the assurance of product quality.
These could later be rearranged as seen in Figure 3 below:
Figure 4: Stations Rearranged in Relation to The Nodes
The design and constructions will be divided up into the FMS for evaluation, the hardware nodes to connect sensors to the QMS. Thereafter the method for implementing the intelligent quality management system will be discussed. Lastly a case experiment will be formulated to evaluate the system.
An IP address identifies the station and a number of IO are setup for that station. The IO setup is to define the digital and analogue inputs that will be getting instructions for the station, and outputs that will be sending out data to the QMS. Certain stations like the Image acquisition station will have an IP camera mounted to perform the vision inspection. The IP will be unique to the camera and is not to be confused with the IP for the station, which this station will also have. The other reason for the IP addresses is to know the order in which the stations are arranged.
1) Flexible Manufacturing System (FMS) The FMS is made up of a number of stations that each have a conveyor belt; with the controls to stop and start it up, as well as sensors. The conveyor belt moves the product through the assembly process as instructed. Sensors on the station will assist in this control. Sensors alert the station and thus the system to the presence of a product. The station communicates with the control system when the product is in position. This initializes a response to stop the conveyor belt and start a task. The task depends on the station. Each station is part of the assembly process, setup to complete a specific task. Tasks will vary between barcode placement, visual inspection and electrical tests. The fact that this is a FMS means that the order of these stations and thus their tasks can change. Additional tasks can also be introduced to the assembly process.
2) Hardware nodes As stated each station will have a predefined task. An Arduino could be set up as a generic hardware sensor node. This will serve as a bridge between the FMS and QMS. Determining and establishing communication that needs to take place in order for the QMS to be of any value to the FMS. The path of communication that will be established is thereafter used to transfer product data from the sample QR codes. The hardware node will ascertain IO connections and types. In other words, determine which IO are connected and which of the connected IO are digital or analogue. Initialisation of the system will be a passive scanning of the IO nodes in order to establish which ones have been connected. A connected input or output means that the system can determine the order of the stations, albeit just an initial assumption to be verified while in learn mode.
Inputs and outputs (IO) of each station are setup to allow instruction signals and data to be exchanged. Inputs to the station will involve an instruction to start or stop the conveyor and an initialization signal for a task. Outputs will signal the presence of a product, the completion of a task as well as send out data related to the task. This data will be product specific for the task such as a successful placement of a QR code, and the QR code details.
3) Quality Management System (QMS) The QMS will be designed to have two modes of operation, namely Learn and Run mode; as shown in Figure 2 below. In learn mode there will be a process of setting up the system. This process of setting up can only be described as a period when the system is “learning”. The QMS; in this mode, will use the data gathered through the process of scanning sample product QR codes to set itself up.
The data from the different stations is send out by the control unit through the IO of each station. These IO can be digital and/ or analogue. The FMS stations however can be rearranged and this means that the order of the data that it send out will also change. This is where the hardware nodes come in. Hardware nodes act as a bridge between the FMS and QMS. Figure 2 shows a possible setup of the stations in relation to the Nodes:
Figure 3: Setup of Stations in Relation to The Nodes
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Figure 5: Flow diagram of the System
Learn mode as already mentioned is a phase when the system is familiarising itself with the products that will be assembled. The QMS will collect all possible data that belongs to the products that will be assembled by the system and analyse it to “make sense” of the product specifications. This is best served with an example. Previously there was reference to an assembly system that produces circuit breakers (CBs), which can fall into three categories namely 5 amperes, 10 amperes and 20 amperes. The QMS in Program mode will be presented with three categories of sample product QR codes relating to the circuit breaker (CB). Within those three categories there will be QR codes for three or more quality CBs (Pass), and another three or more QR codes linked to failed CBs (Fail). The data that the QMS retrieves from scanning the QR codes will be logged into the database and analysed to determine the number of fields that a table will require to store the data for each product. Emphasis here should be given to the fact that there doesn’t have to be products going through the FMS assembly process, but rather product data generated and presented in the form of QR codes for the QMS. The QMS then can go through the data and determine the different categories of CBs, the fields that the product table should have and also the conditions that qualify and disqualify a product.
Figure 6: The QMS Program Mode
During run mode the circuit breaker will be going through the assembly process which should start with the initial unit being assigned a unique identifier. This unique identifier is generated in the form of a QR code with separators indicating the fields that the QMS created when generating a table in the database. Each station will perform a task on the CB unit and also transfer data to the QMS so it is logged into the database and later added to the QR code. The Electrical test for 5 amperes will show a Pass for a well assembled 5 ampere CB but a Fail for both good quality 10 ampere CBs and 20 ampere CBs. This tells the QMS that the type of CB currently in the Electrical Test (5 amp) station is a 5 ampere CB. This is further confirmed because this 5 ampere CB will fail at the 10 ampere and 20 ampere electrical test stations. Good quality is also a matter of how a product is presented and that is where vision inspection comes in and in the FMS Image acquisition and inspection will take place at the station which is equipped with an IP camera. The IP camera is triggered to either take a high resolution image in the case where the product fails to qualify. A low resolution image is requested if the product is successful however. The idea is that more detail on the image needs to be available for the evaluation, so the user can take a closer look at the failed product without the need for the actual product to be in hand. The failed product might be sitting in the rejected pile with numerous others, ready to be repurposed or disassembled.
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followed by the vision inspection, as in Figure 5 above. • Electrical testing; in the order from the most assembled circuit breaker to the least, to determine the circuit breaker category of the product, followed by the vision inspection. • Vision Inspection of the initial product to determine what assembly still has to be done to complete the product, followed thereafter by the Electrical tests. • A varying configuration of new stations introduced to the assembly line; to complete a new task, in order to test the flexibility. Various products can be assembled and inspected by the FMS. The other advantage is the FMS’s ability to adjust to a new product introduced to the system. Sample product data will put this functionality to the test. The initial introduction of a product tests the FMS’s ability to adjust to new products. This also evaluates the QMS, testing the data storage and analysis.
Figure 4 below outlines not only the interfacing that takes place between the QMS and FMS, but also shows the steps that are involved when the QMS is in Run mode.
The QMS is tasked with the evaluation of the FMS and thus data management associated with the product assembly and inspection. The best result from the evaluation of the QMS for sample product data capturing and analysis means getting enough data from the barcodes to build up a profile for the product. This data profile should be a clear indication of what products will be assembled and the different categories that these products fit. Data capturing and analysis during active product assembly is successful when the product can be tested and categorized successfully. This functionality is coupled with the capturing and analysis of product data. The QMS must be able to gather and organize the data as it is collected from the product under assembly. Saving and continuously comparing test and visual inspection data of the product; in the different categories, to ensure that no inconsistencies occur in the product quality.
Figure 7: Flow Diagram of the System in Run Mode
V.
EVALUATION
Based The system would be evaluated with reconfigured line setups in the conveyer line as stated in Flexible Manufacturing System sample construction. Setup of the assembly system will be initialized by the QR code printer and placed on the product. The following configuration and product assembly discussion is in line with the case study on the circuit breaker.
VI.
The manufacturing industry is the basis of a nation’s economy and powerfully influences people’s livelihood. Emerging technologies can have a major impact on manufacturing models, approaches, concepts and even businesses. Improvements in FMS has resulted in the need of a management system that can match the flexibility and also guarantees quality products. The need for an Intelligent Quality Management System for Flexible Manufacturing Systems that can integrate into current manufacturing systems in order to improve manufacturing and industry 4.0 is addressed herein. Proposed is a management system that combines the benefits of a database, a monitoring program, and microcontroller to oversee the FMS and manage the data from it. This system will enable the quick setup of database tables and queries for this purpose after rearrangement of stations. It will also be able to switch between this mode of setup and monitoring the data. Ahead of this is to have these individual parts of the quality management system communicating and working as one, eliminating quality problems that the FMS has.
The first configuration would be as shown in Figure 7:
Figure 8: Initial Configuration of the FMS
Other configurations of the assembly system will be variations in the electrical test order, and the sample data for the product will vary. The following configurations with regard to the FMS are to be considered: •
CONCLUSION
Electrical testing; in the order 5 A -10 A - 20 A, to determine the circuit breaker category of the product,
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