Developing a lean design for Six Sigma through

Int. J. Productivity and Quality Management, Vol. 6, No. 4, 2010

Developing a lean design for Six Sigma through supply chain methodology Ming-Chang Lee* Department of Information Management, Fooyin University, 151 Chin-Hsueh Rd., Ta-Liao Hsiang Kaohsiung County, Taiwan E-mail: [email protected] *Corresponding author

To Chang Department of Information Management, Shu-Te University, No. 59, Hengshan Rd., Yanchao Kaohsiung County, Taiwan E-mail: [email protected] Abstract: The six-sigma systems can promote the enterprise competitive ability, such as pursuing cost improvement, promoting quality, the customer’s satisfaction and valid strategy performance. This paper explored the synergies resulting from the combination of state-of-the art quality initiatives, lean and design for Six Sigma, and develop an integrated SCOR with lean and design for Six Sigma methodologies for their applications to service process improvement and design/or resign. We used the concepts of strength and weaknesses of supply chain operations, lean, and design for six-sigma, for developing a lean design for six-sigma through supply chain model. We discussed a lean and design for Six Sigma through supply chain methodology. Keywords: lean design for Six Sigma; supply chain methodology. Reference to this paper should be made as follows: Lee, M-C. and Chang, T. (2010) ‘Developing a lean design for Six Sigma through supply chain methodology’, Int. J. Productivity and Quality Management, Vol. 6, No. 4, pp.407–434. Biographical notes: Ming-Chang Lee is an Assistant Professor of Department of Information Management at Fooyin University and National Kaohsiung University of Applied Sciences. His research interests include knowledge management, parallel computing, and data analysis. His publications include articles in the journal of Computer and Mathematics with Applications, International Journal of Operation Research, American Journal of Applied Science and Computers, Industrial Engineering, International Journal Innovation and Learning, Int. J. Services and Standards, Lecture Notes in Computer Science (LNCS), International Journal of Computer Science and Network Security, Journal of Convergence Information Technology and International Journal of Advancements in Computing Technology. To Chang is an Assistant Professor and the Chairman of Department of Information Management at Shu-Te University, Taiwan. His qualifications include Master degree in Computer Science from Naval Postgraduate School, USA and PhD in Electronic Engineering from Chung Cheng Institute of Copyright © 2010 Inderscience Enterprises Ltd.

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M-C. Lee and T. Chang Technology, Taiwan. His research interests include information security, management information systems, and enterprise resource planning. His publications include articles in International Journal Innovation and Learning, Int. J. Services and Standards, and International Journal of Computer Science and Network Security.

1

Introduction

Lean production refers to approaches initially developed by the Toyota Motor Corporation that focus on the elimination of waste in all firms, including defects requiring rework, unnecessary processing steps, unnecessary movement of materials or people, waiting time, excess inventory, and overproduction. The root of both lean and Six Sigma reach back to the time when the greatest pressure for quality and speed were on manufacturing. Lean rose as a method for optimising automotive manufacturing; Six Sigma evolved as a quality initiative to eliminate defects by reducing variation in processes in the manufacturing industry. Desai (2008) explains phase wiz application of all the phases of define-measure-analyse-improve-control (DMAIC), and ultimately shows how Six Sigma can help improving productivity as well as profitability. It is not surprising that the earliest adopters of lean Six Sigma (LSS) arose in the service support functions of manufacturing organisations like GE Capital, Caterpillar Finance, and Lockheed Martin (Snee, 2000; Natarajan and Morse, 2009). Linking maintenance excellence and Six Sigma leads to an improved model of the organisation of the maintenance function, enables reduction of variations in the process, eliminates the occurrence errors and reducing the time cycle for the maintenance process (Lazreg and Gien, 2009). LSS for services is a business improvement methodology that maximises shareholder value by achieving the fastest rate of improvement in customer satisfaction, cost, quality, process speed, and invested capital (Su et al., 2006). The fusion of lean and Six Sigma improvement methods is required because: •

lean cannot bring a process under statistical control

•

Six Sigma alone cannot dramatically improve process speed or reduce invested capital

•

both enable the reduction of the cost of complexity.

Ironically, Six Sigma and lean have often been regarded as rival initiatives. Lean enthusiasts note that Six Sigma pays little attention to anything related to speed and flow, while Six Sigma supporters point out that lean fails to address key concepts like customer needs and variation. Both sides are right. Yet these arguments are more often used to advocate choosing one over the other, rather than to support the more logical conclusion that we blend lean and Six Sigma (George, 2002). Wang et al. (2004) applied Six Sigma to supplier development in the supply chain management (SCM). The Voluntary Inter-industry Commerce Solutions Association’s (VICS) collaborative planning, forecasting and replenishment (CPFR) is a process tool to

Developing a lean design for Six Sigma through supply chain methodology 409 improve the SCM. It includes collaborative planning, execution and monitor between all members (VICS, 2006). Fliedner (2003) investigates the traditional supply chain forecasting which some costs are occurred from the inaccurate forecasting. Using CPFR, the inaccurate forecasting problem can be improved. The challenging goal to achieve competitiveness in modern markets begins from business process integration. The processes are actually driven by customer requirements rather than by the internal business gains. In order to meet the final customer requirements, companies are involved in supplier-customer chains (Mazzola, et al., 2007). Knowles et al. (2005) integrate Six Sigma, balance score card and supply chain operations reference (SCOR) into a supply chain conceptual improvement model (SCCIM). Banuelas et al. (2009) description of status of Six Sigma implementation of Six Sigma in the supply chain provides a benchmarking exercise including tools and techniques, fundamental metrics, potential savings and reason for potential failures among others. Design for Six Sigma (DFSS) is a relatively recent approach to product development that focuses on delivering the right product at the right time and at the right cost. DFSS provides a systematic method to build important customer requirements into all related aspects of the product development process that can be measured, verified and optimised. DFSS provides a way for customers to incorporate performance characteristics into their product manufacturing and development processes (Chang and Su, 2007). Manufacturing and development processes can then be optimised to meet those customer requirements using specific and quantifiable metrics. DFSS is a separate and emerging business-process management methodology related to traditional Six Sigma. DMAIC Six Sigma may still be used during depth-first plunges into the system architecture analysis; DFSS provides system design processes used in front-end complex system designs (Chowdhury, 2002). LSS and DFSS methodologies have been successfully applied in a variety of industries 1

to improve performance

2

to design new products, processes and services

3

to redesign the existing ones (Jugulum et al., 2009).

lean and DFSS disciplines have been popularised because their successful implementations by many world-class organisations around the world to improve business processes and reap substantial benefits of cost savings. DFSS works on the early stages of the process life cycle and utilises the most powerful tools and methods presently known for developing optimal service design. It was found in a literature study that although it is possible to have independent successes in lean, DFSS, and SCOR, each magnifies the strengths of the other while compensating for the weaknesses when integrated in an overall improvement or design strategy. Therefore, the motivation for this paper is to develop an integral lean, DFSS and SCOR methodology for improving the efficiency and quality of their business activities in the supply chain continuously. The rationale for the combination of the three methodologies are also examined and justified on theoretical basis. A well-proven DMADV and lean techniques are used to develop a LSS strategy, and a conceptual framework of the LSS methodology through supply chain design. The research framework is illustrated in Figure 1.

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Figure 1

The research framework

Service process improvement or design/redesign

Design/redesign of SCOR, lean DFSS converge

Lean methodology

2

SCOR methodology

DFSS methodology

Lean

In the 1970’s, we ‘discovered’ the Toyota production system (TPS). Since then, many companies have adopted TPS or ‘lean manufacturing’ methods, realising enormous cost savings while improving competitive position. Now we are finding that lean manufacturing is not enough to stay competitive (Sanchez and Perez, 2001). The basic problem with traditional product development processes is that most of the cost is locked in long before production launch. Products that do not reach out to customers in terms of price, performance, and benefits do not sell well. In short, designs that arrive at the factory late, with poor production yields, major manufacturing problems, and unresolved engineering problems, undermine the benefits of lean manufacturing. Lean is a strategic approach to change and improvement. Focusing just on the tools at an operational level and reducing cost, will not obtain the full benefits (Miller, 2005). The overarching benefit of lean is the ability to see cost and lead time reduction opportunities where you never saw before. Through application of the lean concepts and tools, the process step once through essential are unnecessary, and their costs and delays removable after lean tools have been applied (George, 2003). The most important advantages of lean production are speed and timing. Applying standard lean tools to the new product development process will certainly reduce development lead-time. By taking a broader view of new product development, we can simultaneously minimise manufacturing lead-time, maximise product performance from the customer’s viewpoint, and maintain target cost. There are many existing tools and methods that can help your company achieve a high level of synergy and performance in product design. To be effective, tools and methods must be applied at the appropriate points in an integrated product development process (Sahin, 2000; Smith and Adams, 2001). Lean is an approach that seeks to improve flow in the value stream and eliminate

Developing a lean design for Six Sigma through supply chain methodology 411 waste. The evolution of lean approach is cell and line, shop floor, value stream and value system. The evolution of the lean approach denoted as Table 1 (Gibbons, 2008; Grewal, 2008). Table 1

Evolution of the lean approach

1980–90 Cell and line Highly prescriptive tool-based approach, disseminating the tools used by Toyota and others

1990–mid 1990 Shop floor Highly prescriptive best practice approach, with a focus on quality

Mid 1990–1999 Value stream

2000+ Value system

Lean principles value stream mapping.

Contingency involving customer value, policy deployment, size, industry, technology focusing on system-level capability and integrated processes

The concept of the lean enterprise with a focus on quality, cost and delivery. Concept of ‘one best way’ still prominent – ‘what would Toyota do?’

We utilise a seven-step lean design process as an integrated product development process. The seven-step lean design process is an integrated approach to new product development. It will reduce your time to market and improve the market acceptance of your new products. It will capture manufacturing cost reductions that are inaccessible to after-the-fact applications of lean and Six Sigma. Lean design represents a powerful competency that is guaranteed to improve your organisation’s competitive position. Step 1

Define product

Define as clearly as possible what the market desires, without either overshooting or undershooting on performance, features, and quality. Voice of the customer (VOC) tools are applicable during this first step. Tools and methods to consider are: •

a lean and more efficient version of quality function deployment (QFD)

•

probe-and-learn feedback techniques

•

market or customer surveys

•

focus groups

•

Kano methods are used to identify spoken and unspoken customer needs.

Step 2

Establish product line optimisation team (PLOT)

With a reasonably clear product definition in hand, your company can convene an appropriately chartered PLOT. This team considers how the new product will fit within existing material inventory, processes, factory layout, core competencies, etc. Process capability is evaluated against proposed specifications. The PLOT provides specific recommendations for enhancing the synergy and manufacturability of the product to the development team at the project. The PLOT also develops a product roadmap to guide product development through the expected life cycle of the product line.

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Step 3

Determine target cost

Once the project is underway, design requirements are prioritised based on customer benefit and need. A target cost is established. The team develops a preliminary cost model to put into the target cost. This is a tool that designers can use early in the conceptual design. This model will evolve over time to become an accurate representation of the actual cost-at-volume for the new product. The target cost should be used iteratively through product development is as Figure 2. Figure 2

The target cost through product development

Start Target cost (CT) is determined

No

Continue designing unit more cost data is known

Actual cost (CA) is estimated

Is CA< CT?

Yes

Apply lean tools to reduce actual cost Step 4

Translate requirements into specifications

The design team uses value engineering techniques to generate a broad and innovative list of design alternatives for the new product. Toyota and others have successfully used this ‘set-based’ approach to generate and consider a broad spectrum of possibilities before selecting the final concept. The design team uses a simple cost/performance tradeoff tool to determine which concept has the best combination of manufacturing cost and customer value. To ensure the final design choice represents the best balance between customer needs, quality and cost, the team evaluates alternative designs against twenty cost factors in five categories: •

direct labour

•

direct materials

•

assignable capital

•

design costs

•

factory overhead.

Developing a lean design for Six Sigma through supply chain methodology 413 Step 5

Design at system level

Upon arriving at an optimal concept, the design team consults the product line roadmap. From this forward-looking document, the team identifies opportunities to extend and customise the product. Platform design considerations are incorporated into the rapidly solidifying design. The team also considers scalability, modularity, and mass customisation strategies as ways to capture economies during future product line expansion. Step 6

Design at detail level

As detailed design begins, the team determines the compatibility of the new design to existing and planned manufacturing processes. To optimise design variables or controllable process parameters, the team uses a powerful Six Sigma methodology called design of experiments (DOE). DOE is the only method capable of dealing successfully with the usual situation of multiple design and process variables having interactive effects on product performance. The traditional practice of testing one variable at a time is ineffective in this situation, even counter-productive. DOE has the additional capability of ‘robust design’ – designing a product to perform consistently in the face of uncontrolled manufacturing or use-environment factors. Step 7

Production preparation process

To ensure smooth and rapid transition of the new design to the factory, the team considers the manufacturability of the product from the standpoint of touch labour, standard materials, cell-layout, take time, capacity, etc. A model for this ‘production preparation process’ (3P) has recently emerged from studies of the ‘Toyota way’. An adoption of this comprehensive process is used by the team to ensure smooth and rapid transition of the new design to the factory. The goals of 3P are design products for lean production, incorporate error-proofing and JIT, guarantee process capability and cycle time, and build-quality into the system (see Figure 3). Figure 3

Toyota’s production preparation process

Information phase -Part numbers -Drawings -Samples -Volumes -Ramp schedule -Process steps -TAKT time

Creative phase

Redefine phase

-Alternative Processes -Model cells -Simulation

-Flow chart -TAKT time -Cycle time -Process capacity -Standard work -Standard layout

Launch to production

Lean production focuses on the identification and elimination of the seven wastes in every worker’s area every day, using JIT concept to create a pull system over time. A pull system is a dramatic innovation when compared to traditional push systems. It minimises

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inventory, work-in-process, and raw material in a manufacturing process. Table 2 illustrates the techniques of lean product improvement methodologies (principle) and lean product techniques. Table 2

The lean product improvement methodologies (principle) and techniques

Lean production principles • Identification and elimination (seven elements of waste) • Produce product only on demand (just-in-time) • Understanding the customer • Continually simplify the production process • Minimal inventory, work-in-process, and raw material • Optimising the use of manufacturing resources

Lean production techniques •

Pull system through the plant

•

Visual management

•

Value stream mapping

•

Team-based Kaizen activities

•

Standardisation for each work activity

•

Mistake-proofing

•

Cellular manufacturing

•

Kanban production control system

•

Group technology

•

Single minute exchange of dies (SMED)

•

Total product maintenance (TPM)

•

5S

•

Work flow balancing

•

TSKT time (one piece flow)

•

Set up time reduction (quickly changeover)

•

Workforce reduction

•

Spaghetti diagram

•

Plant layout

Source: Pyzdek (2003) and Burton (2001).

3

Design for Six Sigma

Six Sigma initiatives have achieved recent popularity because of their bottom line focus versus previous TQM initiatives which often tended to be unfocused (Etienne, 2009). General Electric, one of the leaders in Six Sigma programs defines its key elements as: •

Critical to quality: attributes most important to the customer

•

Defect: failing to deliver what the customer wants

•

Process capability: what your process can deliver

•

Variation: what the customer sees and feels

•

Stable operations: ensuring consistent, predictable processes to improve what the customer sees and feels

•

Design for Six Sigma: designing to meet customer needs and process capability

Developing a lean design for Six Sigma through supply chain methodology 415 Lean design for Six Sigma (LDFSS) will ensure your product and service development experts launch the right products and services with the right features for the right market the first time. DFSS is a separate and emerging business-process management methodology related to traditional Six Sigma. DFSS has the objective of determining the needs of customers and the business, and driving those needs into the product solution so created. DFSS is relevant to the complex system/product synthesis phase, especially in the context of unprecedented system development. It is process generation in contrast with process improvement ideal for both companies that have implemented Six Sigma or already use advanced design methodologies. DFSS is often used when the existing processes do not satisfy the customers or are not able to achieve strategic business objectives (Eckes, 2001; Thomas and Singh, 2006). DFSS has successfully been implemented for product design in number of leading manufacturing firms such as Motorola, GE, Allied Signals, Honeywell, and Seagate, while a lack of examples is found of designing services within a supply chain (Haik and Roy, 2005). DFSS, lean production development and lean knowledge management are three effective methodologies in improving a product development process. DFSS can greatly improve product value and quality. Lean product development and lean knowledge management can help to achieve better product development lead time and efficiency by reducing wastes (Yang and Cai, 2009). Define-measure-analyse-design-verify (DMADV), is sometimes synonymously referred to as DFSS. The traditional DMAIC Six Sigma process, as it is usually practiced, which is focused on evolutionary and continuous improvement manufacturing or service process development, usually occurs after initial system or product design and development have been largely completed. DMAIC Six Sigma as practiced is usually consumed with solving existing manufacturing or service process problems and removal of the defects and variation associated with defects. On the other hand, DFSS (or DMADV) strives to generate a new process where none existed, or where an existing process is deemed to be inadequate and in need of replacement. The relationship of DMAIC with DMADV is showed as Figure 4. There are five steps in the DMADV process, they include; define, measure, analyse, design details and verify the design. Here is some more information regarding each step. •

Define: In the first step, you must define the design goals that are both consistent with your customer’s demands and your own company’s goals.

•

Measure: In this step, four things should be measured. They include, CTQ’s which stand for critical to qualities, production process capability, risk assessments and product capabilities.

•

Analyse: It is important to use the process of analysis to develop and design better alternatives that can reduce defects. These designs must be evaluated for their inherent capabilities to determine whether the design is the best available or if an alternative can be created which may be better.

•

Design details: In this step a design must be optimised to function at its peak. In addition, in order to optimise a design, a design must usually be verified. While verification is the last process, during the design details step, a design plan should be readied for the next step.

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M-C. Lee and T. Chang Verify: Once a design has been analysed and tested, it should be verified. Verification usually occurs through pilot runs. As a design is verified through the pilot run, it can be readied for full production.

Figure 4

The occasions using DMAIC and DMADV methodologies

Source: Modified Pyzdek (2003)

3.1 Similarities between DMADV and DMAIC (Cronemyr, 2007) •

two of these Six Sigma methodologies talks about reduction of DPMO (defects per million opportunities)

•

both DMADV and DMAIC use the same kind of Six Sigma tools (like, DOE, QFD, TREEZ, Pugh matrix etc.)

•

customer’s needs are the basic driving parameters for both Six Sigma methodologies

•

Six Sigma black belt (BB) and master black belt (MBB) play important roles in implementation for both the cases

Developing a lean design for Six Sigma through supply chain methodology 417

3.2 Differences between DMADV and DMAIC (Cronemyr, 2007) •

DMADV can be thought of for either designing of completely new product/process or substantial redesign of an existing product. On the other hand, DMAIC is used for modifying or fine tuning some existing processes in order to make it inline with customer requirements.

•

Measure phase of DMADV deals with quantifying customer’s needs to make specifications. However, measure phase of DMAIC deals with measuring current performance level of existing process.

•

Analyse phase of DMADV deals with comparing and finalising possible solutions with respect to customer needs by using tools like Pugh matrix etc. Analyse phase of DMAIC tries to figure out root cause of process deviation.

•

Improve phase of DMAIC eliminates the defects from the existing process and align them with customer’s expectations. Design phase of DMADV deals with building new Six Sigma product/process.

•

Validate phase of DMADV ensures that newly developed products/processes conform to the customer’s needs. The control phase of DMAIC ensures that a modified process won’t deviate further from its current performance level.

Six Sigma is all about improving efficiencies and reducing costs of existing products. DFSS on the other hand, is about the design, development and commercialisation of new products and processes. It is about growth, revenue and profitability. Unlike Six Sigma that requires a small focused team. DFSS and new product development requires a dedicated, long-term cross functional team that typically includes business, marketing, technology, engineering, manufacturing, sales and many other support functions. There is a misconception that like Six Sigma, DFSS is a turnkey system that can be immediately incorporated and implemented with quick return on investment. The DFSS and new product development process must be tailored to that unique combination of factors for the initiative to be relevant and sustainable. Table 3 summarised the important differences between Six Sigma and DFSS. Table 4 summarised the DFSS methodologies (principle) and DFSS techniques. Table 3

Differences between Six Sigma and DFSS

DMAIC: define, measure, analyse, improve, control

DMADV: define, measure, analyse, design, verify DMADOV: define, measure, analyse, design, optimise, verify

Look at existing processes and fixes problems

Focuses on the up-front design of the product and process

Small project team

Multidisciplinary product team

Deal with one or two customer

Deal with multiple customer requirements at one

More reactive

More proactive

Dollar benefits obtained from Six Sigma can be quantified rather than quickly

Benefits are more difficult to quantify and tend to be more long-term. It can take six to 12 months after the new product before you will obtain proper accounting on the impact.

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Table 4

The DFSS principles and techniques

DFSS principles

DFSS techniques

•

Focus on proactive

•

VOC and survey design

•

Design of new products or services and process

•

Kano model and survey

•

•

Quality function development

Focus on marketing, R&D, and design

•

•

Project and design scorecard

Involves greater cultural change

•

•

Introduction to TRIZ and ASIT

Team work is cross-functional

•

•

Morphological analysis

Increase a customer satisfaction

•

•

Pugh’s concept selection

Increase in profit over the product lifecycle

•

•

Axiomatic design

Reduction in defects and variability in product development process

•

Boundary diagram

•

Function definition

•

Part-to-function matrix

•

Function-driven design FMEA

•

Value analysis (VA/VE)

•

Parameter diagram

•

Design VMEA

•

Enhanced robustness planning

•

Robustness demonstration matrix

•

Taguchi robustness

•

Design of experiments

•

Verification and validation

•

Statistical tolerance

•

Increase in productivity

•

Reduction in product development time and development cost

3.3 Benefits of DFSS •

increase customer satisfaction, revenues and profit

•

differentiated and high quality new products

•

cycle time reduction and speed to market

•

flexibility to respond to new market requirements, application and regulations

•

better assessment of risks through the product development cycle

•

sustainable products and processes

•

effective communication, portfolio management, resource management and project management.

4

SCOR with lean and DFSS

The SCOR-model is a process reference model that has been developed and endorsed by the Supply Chain Council as the cross-industry standard diagnostic tool for SCM. SCOR

Developing a lean design for Six Sigma through supply chain methodology 419 enables users to address, improve and communicate SCM practices within and between all interested parties. SCOR is a management tool. It is a process reference model for SCM, spanning from the supplier's supplier to the customer’s customer. The SCOR-model has been developed to describe the business activities associated with all phases of satisfying a customer’s demand. By describing supply chains using process building blocks, the model can be used to describe supply chains that are very simple or very complex using a common set of definitions. As a result, disparate industries can be linked to describe the depth and breadth of virtually any supply chain. The model has been able to successfully describe and provide a basis for supply chain improvement for global projects as well as sitespecific projects (Deo, 2005; Mazzola et al., 2007).

4.1 The advantages and critique of SCOR SCOR is a model developed and endorsed by the Supply-Chain Council (SCC) as the cross-industry standard for SCM. SCOR defines the supply chain as the integrated processes of plan, source, make, deliver, and return, spanning from your suppliers’ supplier to your customers’ customer, aligned with operational strategy, material, work, and information flows. The model builds its strength by linking process elements, metrics and best practices associated with supply chain execution. Some of the advantages of using the SCOR model for a supply chain improvement initiative are: 1

standardised model and framework that provides a common language to communicate supply chain definition, metrics and best practices for all interested parties

2

structured methodology to align business and supply chain strategies and determine targets for supply chain improvements to meet business objectives

3

standardised multi-level process performance metrics

4

level 1–3 material, work and information flow analysis

Critique of the SCOR model includes 1

inadequate organisation wide training

2

few metrics associated with the organisational development (employee learning) aspect of a balanced scorecard

3

few analytical tools for problem solving and execution of improvement projects identified by SCOR.

4.2 SCOR model consists of five major process workflows A major goal of applying a SCOR model is to develop a value stream map describing a supply chain’s major process workflows. SCOR model consists of five major process workflows (see Figure 6). These are:

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1

demand and supply planning

2

warehousing and delivery

3

sourcing strategies

4

reverse logistics

5

transformation processes.

SCOR consists of several hierarchal levels. These include an evaluation of strategic goals and objectives in a context of competitive supply chain analysis, value stream mapping (VSM) of major process workflows and at the lowest level an operational analysis of work tasks, standards and metrics. However, the usefulness of a SCOR model is that it can be customised to fit the specific supply chain of almost any organisation, but, major process workflows are standardised and include basic control elements based on the combined knowledge of many industry experts.

4.3 SCOR with lean and DFSS Building a supply chain model or process with using a highly standardised structure enables an organisation to detect and eliminate process variation. This is because variation from a well-known standard is easily detected, analysed and eliminated using lean, Six Sigma or designs Six Sigma and similar improvement methodologies. This concept is shown in Figure 5 at the second and third levels of the pyramid. Figure 5

SCOR model’s hierarchal levels

Developing a lean design for Six Sigma through supply chain methodology 421 Figure 6

5

SCOR model’s five major process workflows

The rationale for combination lean with DFSS

DFSS seeks to avoid manufacturing/service process problems by using advanced VOC techniques and proper systems engineering techniques to avoid process problems at the outset (i.e., fire prevention). When combined, these methods obtain the proper needs of the customer, and derive engineering system parameter requirements that increase product and service effectiveness in the eyes of the customer. This yields products and services that provide greater customer satisfaction and increased market share. These techniques also include tools and processes to predict, model and simulate the product delivery system (the processes/tools, personnel and organisation, training, facilities, and logistics to produce the product/service) as well as the analysis of the developing system life cycle itself to ensure customer satisfaction with the proposed system design solution (Chase et al., 2000). In this way, DFSS is closely related to systems engineering, operations research, systems architecture and concurrent engineering. DFSS is largely a design activity requiring specialised tools including: QFD, axiomatic design, TRIZ, DOE, Taguchi methods, tolerance design, robustification and response surface methodology. While these tools are sometimes used in the classic DMAIC Six Sigma process, they are uniquely used by DFSS to analyse new and unprecedented systems/products. The following represents our more specific list of elements of the DFSS framework: 1

understand real customer needs through VOC analysis

2

use QFD to translate customer needs into critical technical characteristics of the product and ultimately into critical to quality (CTQ) characteristics of the product and process

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3

focus on designing for the lifecycle to minimise lifecycle costs with design for manufacturing and assembly (DFMA), value analysis and target costing and to enhance reliability with design for reliability and design for test (DFT)

4

mistake-proof the product and process

5

perform failures modes and effects analysis (FMEA) or anticipatory failure determination (AFD) to identify potential failures and take corrective action to mitigate or prevent those failures. FMEA and AFD apply to both the design of the product and the design of the process

6

develop capable manufacturing processes and select processes that are capable of meeting the design requirements, especially with CTQ parameters

7

use DOE or Taguchi methods to optimise parameter values and reduce variation, in other words, develop a robust design

8

verify and validate the product design will meet customer needs with peer reviews, checklists, design reviews, simulation and analysis, qualification testing, production validation testing, focus groups and market testing

9

measure results with DFSS scorecard; estimate Sigma – do results meet quality target?.

5.1 The strength and weaknesses of SCOR, lean, and DFSS The SCOR model only focused on supply chain processes; it is incomplete in its description of all business process. Key processes and functions missing from the scope of the model include sales and marketing, research and technology development, product development, and some elements of post-delivery customer support. SCOR also assumes but does not specifically address training, quality, information technology (IT), and administration. In the evolution of SCOR deployment methodology, the most critical failure modes associated with application of the model are tied to the following weaknesses 1

inadequate top-to bottom organisation training and development to enable full utilisation of the model within a company

2

few formal analytical techniques that can be used for diagnosis of root-cause process problems

3

inadequate tools, methodologies and techniques to ‘implement’ the improvement opportunities which SCOR identifies.

The advantages of using lean as a process improvement methodology are: 1

structured methodology for waste identification and elimination in any process

2

organisation wide training and involves employees at all levels

3

focused and rapid process improvement and cost reduction

4

structured project management approach and helps communicate customer defined value to all levels of organisation.

Developing a lean design for Six Sigma through supply chain methodology 423 5

Strong analytical tools to map the process and identify root-causes

Critique of lean methodology includes: (Hines et al., 2004) 1

few tools for focusing lean efforts on strategic and operational process priorities

2

inadequate analysis of financial expectations and accountability for bottom-line results

3

lacks an overall supply chain discipline

4

lack of strategic perspective (at least until recently).

The main drawback of using lean alone as a process improvement methodology is lack of strategic supply chain direction. Lean efforts will certainly yield results but can lead to islands of excellence within an organisation if used alone and the time from effort to any significant results can be long. Table 5 summarised methodology strength and weakness of SCOR, lean and DFSS. Some of the advantages of Six Sigma as an improvement methodology are: (Revere et al., 2006) 1

structured methodology and approach for defect and variance reduction in any process

2

dedicated roles, responsibilities, and program infrastructure

3

organisation wide training and development

4

customer and data driven problem solving

5

rigid project tracking and financial accountability for results.

Critique of Six Sigma methodology includes: (Hines et al., 2004) 1

lacks alignment of project execution with strategic and operational priorities

2

no methodology to develop understanding of relationships between projects

3

data dependent tools and techniques difficult to use in situations where data is not available or readily collected

4

processes improved independently

5

lack of consideration for human factors.

5.2 The rationales for combination lean with DFSS Now take a close look at the strengths and weaknesses of SCOR (see Table 5 below). It quickly becomes clear that SCOR methodology fills a major need in a lean and Six Sigma program – identification, prioritisation and strategic alignment of project opportunities with the capability to execute them. The philosophy of lean provides the strategy and creates the environment for improving flow and eliminating waste. Empowered staff are encouraged to continuously improve to create value adding opportunities that otherwise would not be identified. DFSS helps to quantify problems, makes evidence based decisions, helps to understand and reduce variation and identifies root causes of variation to find sustainable solutions.

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A combination of both can provide the philosophy and the effective tools to solve problems and create rapid transformational improvement at lower cost, potentially, this could increase productivity, improve quality, reduce costs, improve speed, create a safer environment for patients and staff and exceed customer expectations. Table 5

The strength and weaknesses of SCOR, lean and DFSS Methodology strength

SCOR Structured methodology for alignment of strategic and operational metrics and goals to identify business improvement opportunities Standardised supply chain process reference model and framework standardised multi-level process performance metrics industry and competitive benchmark data sources ‘Macro-level’ approach or identification of improvement opportunities Level 1–3 material, work and information flow analysis Source for best-in-class SCM practices Can be used to identify enabling IT capabilities to optimise the supply chain Opportunity and project portfolio with detailed ROI analysis Inadequate organisationwide training and development Few analytical tools for cause effect analysis and problem solving at the ‘macro-level’ Inadequate tools, methodologies, or techniques to focus on executing projects identified by the SCOR efforts Little programmatic infrastructure for organising and managing concurrent project activities

Lean

DFSS

Structured methodology for diagnosing and executing waste elimination projects in any process Typically focused on a factory/cell/process level scope Focus on workplace organisation (5S) and preventative techniques (PTM) Level 4 + material, work and information flow analysis Concurrent training/projects – applied skills development Best-in-class operating practices at a factory and cell level Standard work development Visual controls and cell management tools for control of new processes Very effective at rapidly reducing cost – through waste elimination Few tools for focusing lean efforts on strategic and operational process priorities Inadequate program infrastructure and training to drive breakthrough improvement Poor capability for addressing support system issues and transactional processes Inadequate analysis of financial expectations and accountability for bottomline results No tools or capability to remove bottlenecks driven by process variability/defects

Structured methodology for diagnosing and executing defect and variation reduction projects in any process Dedicated roles, responsibilities, and program Infrastructure Top-to-bottom organisation training and development highly structured problem solving approach (DMADV) Level 1–4 + variation and defect reduction techniques Concurrent training/projects – applied skills development Customer and data driven decision making Unique methodologies for product development, operations, and transactional applications Rigid project tracking and financial accountability for results No specific methodology for aligning strategic and operation priorities with project execution and candidate selection No methodology to develop understanding of the confounding relationships between projects Inadequate ‘macro-level’ analytical techniques to validate projects Data dependent tools and techniques difficult to use in poorly controlled and wasteful operating environments

Developing a lean design for Six Sigma through supply chain methodology 425

6

Developing a LDFSS through supply chain methodology: SCOR, lean and DFSS converge

SCOR essentially brings a supply chain strategic focus and alignment of business and supply chain strategy. The strong fact-based, data-driven problem solving approaches that lean and DFSS have help to discover ‘root causes’. Additionally, lean brings focus to the customer value. SCOR – assists companies in making many of the major decisions that will affect the general construct of their supply chain and such decisions will have a major impact on the resulting supply chain(s) and its performance and offers a relatively quick return on investment (ROI). Lean and DFSS a complement and strengthen the SCOR-based strategic decisions by providing a continuous improvement philosophy. VSM, part of the lean methodology, can be effectively used to map the workflow and transactions which are specific to each company, adding considerable detail to support a deeper understanding of current and future state processes. For an organisation, using all the three approaches leads to a holistic process improvement methodology. DFSS is the application of Six Sigma principles to the design of products and their manufacturing and support processes. In one respect, DFSS is the repackaging of many quality tools and techniques appropriate for product development into a framework. This framework contains many of the same elements as the advanced product quality planning (APQP) process used in the automotive industry. Often the acronyms DMADV or identify, design, optimise and validate (IDOV) are used to describe the DFSS process. Figure 7 (SOCR, lean, and Six Sigma converge) provides the unique and common strengths of the three methodologies discussed. It is quite evident that these methodologies are complimentary and their individual weaknesses are resolved by their convergent strengths. We recommend starting with SCOR and using the supply chain excellence (SCE) approach to understand your various supply chains, their construct and priorities. Table 6 is the task of SCOR, lean and Six Sigma. Figure 7

SCOR, lean, and Six Sigma converge (see online version for colours)

Source: Kent and Attri (2007)

426 Table 6

M-C. Lee and T. Chang The task of SCOR, lean, and DFSS

SCOR -Strategic alignment -Standard supply chain definition -Metrics and benchmarking -Best practices -Process map -Strategic planning -Process management -Process infrastructure

-Process decomposition -Operational specification -Data driven -Roles and responsibilities

Six Sigma/DFSS -DMAC -Signal level -Reduce variation -DFSS -Hypothesis testing -Statistical sampling

-Process management -Process infrastructure -Quality focus -VA vs. NVA -Problem solving -Training -Process decomposition -Operational specification -Data driven -Roles and responsibilities

Lean -Eliminate waste -Reduce inventory -Local levelling -JIT -Visual control -Process map -Strategic planning -Process management -Process infrastructure -Quality focus -VA vs. NVA -Problem solving -Training

Since the rationale for blending lean and DFSS through supply chain has been demonstrated, the next step is to develop an applicable lean and DFSS methodology. A well-proven DMADV technique is used to develop a LDFSS strategy, and a concept framework of lean Sigma methodology through supply chain (see Figure 8 and 9). Figure 8

A concept framework of LDFSS through supply chain methodology

Developing a lean design for Six Sigma through supply chain methodology 427 Figure 9

7

A concept framework of LDFSS to product development

Lean and design for Six Sigma through supply chain methodology

A conceptual framework of the LDFSS methodology through supply chain that we designed in this research is presented in Figure 8. The descriptions of each step in the methodology are given in further detail.

Phase 1 Supply-chain reference model Step 1

Strategic goals and competitive analysis

A firm’s strategic goals drive business strategy and address the key success factors of the industry. Strategic goals often include the vision or mission statement for the business. They should also set the direction and standard for financial and market results against which actual performance can be measured. The two most common strategic goals are: 1

competitive and market goals that define market share or market growth and penetration for the firm’s products or services

2

financial performance in terms of key ratios, like return on investment and sales, and growth in revenues and/or profitability.

The definition of business strategy includes six areas of analysis. The product-market focus is the first step. The underlying capabilities in implementing a product-market strategy include the technologies, processes and market access that a firm has. These address the business and its key success factors. Businesses strategy includes customer

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targeting, product lines and positions, technical capabilities, strategic processes, and market access. 1

Describe the customer targeting strategy and its requirements. Without targeting a specific customer segment, it is impossible to develop effective products or services that meet specific customer needs and requirements. Each segment, by definition, has a different set of requirements. While differences may be minor at time, they affect the decision of the customer to purchase the product or service.

2

Describe the product line and product positioning strategies for the market segment. The business unit must decide what it will offer and how those offerings will be positioned within the competitive environment. A firm can have one product or a product line that covers a range of prices with a variety of features. The pricequality-performance position is a relative determination compared with competitors' prices, quality levels and features when comparing your products with alternative products in the marketplace.

3

Identify the technologies required to implement the product-market strategy. Technologies provide the basic capabilities needed to develop products or services, as well as the associated processes used in developing or delivering them to the marketplace. Technology determines the range of products and speed with which they can be developed and delivered to the marketplace.

4

Identify the strategic process required to implement the product-market strategy. The core capabilities of a firm are embedded in the business processes and functions. Strategic processes can either improve the product or marketing capabilities of a firm. These processes and functions are the basis of a firm’s competitive strengths and weaknesses, and make up the core competencies of the firm.

5

Identify the market access strategy. The final element of strategy requires that a firm have access to its market or customers. Today, the Internet is considered the new channel for accessing markets.

Step 2

Mapping process workflow and operational analysis

Process mapping and analysis can be an extremely powerful diagnostic tool for your organisation. By analysing the flow of work and information you will not only find process issues, but also uncover structural problems, poor controls, and people issues. You will learn to tap into employee frustration to fix processes and get to the root cause of quality and timeliness issues.

Phase 2 Define/identify value Step 1

Draft a project charter (Pyzdek, 2003)

This step describes the project goals and links each of them with related, measurable project objectives. Measurement criteria for each objective must also be included because they will be used to conform that an objective has been achieved. In addition, business

Developing a lean design for Six Sigma through supply chain methodology 429 outcomes to be derived from the project goals and objectives are to be presented as outlined in the business case. Step 2

Identify the VOC/the customer value

In this step, understand real customer needs through VOC analysis. Step 3

Translate the VOCs into measurable requirements

Using tools like QFD, VOC translated into design specifications termed as critical to customer requirement (CCRs), comprehendible to the supply chain development/design team (Buss and Ivey, 2001). While QFD is the major tool in identify phase, there are other tools that may be used, such as Kano model, Pareto analysis, affinity diagram, values engineering, brainstorming and benchmarking (Rate, 2002). Step 4

Identify critical-to-quality characteristics (CTQs)

CTQs are: 1

element of a process or practice that has a direct impact on its perceived quality

2

the key measurable characteristics of a product or process whose performance standards or specification limits must be met in order to satisfy the customer.

They align improvement or design efforts with customer requirements. CTQs represent the product or service characteristics that are defined by the customer – internal or external. They may include the upper and lower specification limits, or any other factors related to the product or service. A CTQ usually must be interpreted from a qualitative customer statement to an actionable, quantitative business specification (Snee and Hoerl, 2003).

Phase 3 Measure/VSM In this phase it is importance to quickly understand what the inputs and outputs are of processes. In the measurement phase, typically use tools such as VSM, motion and time study, process mapping, measurement systems analysis, and cause and effect (Nave, 2002; Gorge, 2002). VSM is a visualisation tool oriented to the Toyota version of lean manufacturing (lean production system). It helps to understand and streamline work processes using the tools and techniques of lean manufacturing. Step 1

Create a data-collection plan and gather data

We developed a data-collection plan to determine such issues as sampling frequency, which will perform the measurement, the format of data-collection form and the measuring instruments. Then collect data in order to measure the CTQs for the service encounters which are under observation. Step 2

Construct a current-state value stream map

VSM is a critical tool for your lean implementation. It provides a roadmap for change, from which you can build your implementation plan for becoming a lean enterprise. In fact, without a value stream map, businesses often are pursuing lean via only ‘point improvement’, which does not lead to systemic change.

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This is vital both to understand the need for change and to understand where opportunities exist. Step 3

Construct a future-state value stream map

A future state value stream map is the ideal, and an improvement plan to move from the current state towards the ideal future state. A future-state value stream map deploys the opportunities for the improvement identified in the current-state map to achieve a higher level of performance. Step 4

Develop a detailed process map

Taking the future state map consider an action plan that could be implemented to change the current process to the future state.

Phase 4 Analyse/determine root causation In this phase, we use both lean and DFSS techniques to analyse the process. Some lean tools are feasible and powerful for improvement personnel in this phase. Principle analyse phase include TAKT time/cycle time, TRIZ, 3P, failure mode effects analysis (FMEA), control charts, and spaghetti diagram (Sahin, 2000; Burton, 2001). Step 1

Conduct data and process analysis

Step 2

Determine root causes of non-value-added steps

Step 3

Determine the significant root causes

Step 4

Develop transfer function

A transfer function (also known as the network function) is a mathematical representation, in terms of spatial or temporal frequency, of the relation between the input and output of a (linear time-invariant) system. With optical imaging devices, for example, it is the Fourier transform of the point spread function (hence a function of spatial frequency) i.e., the intensity distribution caused by a point object in the field of view. Step 5

TAKT time/cycle time

TAKT time can be defined as the maximum time per unit allowed producing a product in order to meet demand. It is derived from the German word Taktzeit which translates to cycle time. TAKT time sets the pace for industrial manufacturing lines. In automobile manufacturing, for example, cars are assembled on a line, and are moved on to the next station after a certain time – the TAKT time. Therefore, the time needed to complete work on each station has to be less than the TAKT time in order for the product to be completed within the allotted time.

Phase 5 Design detail/flow and pull After the collected data is analysed and conclusions are reached, this phase must be implemented so that the overall process is enhanced. In the phase, typically use tools such as cell design, group technology, line balancing, DOE/quality engineering, and SPC (Moore, 2000; Sahin, 2000; Burton, 2001).

Developing a lean design for Six Sigma through supply chain methodology 431 Step 1

Eliminate the significant root causes

Select a solution to eradicate the significant root causes that have the most impact on the CTQs. Step 2

Develop a pull system

A pull system is where processes are based on customer demand. The concept is that each process is manufacturing each component in line with another department to build a final part to the exact expectation of delivery from the customer. Step 3

Optimise

DFSS stresses predicting and optimising the probability of the design to meet the required targets given environmental variation, manufacturing variation, and usage variation. Statistical analysis and optimisation of design is necessary to achieve a robust product/service design.

Phase 6 Verify/pursue perfection This phase is designed to help the improvement teams confirm the results and make the gains lasting. In the phase, typically use tools such as 5S, task tracking, checklists, hand-off training, control plan, SOP, knowledge management, productivity, and shareholder value (Lathin and Mitchell, 2000; George, 2002). Step 1

Develop a control plan

The purpose of this step is to make sure that the solutions endure. In addition, the control of the service delivery process must occur at both the strategic and tactical levels. Step 2

Implement the control plans

It is needed to keep track of the process performance after improvement, also to control the critical variables relating to performance. Step 3

Productivity

Productivity refers to metrics and measures of output from production processes, per unit of input. Labour productivity, for example, is typically measured as a ratio of output per labour-hour, an input. Productivity may be conceived of as a metrics of the technical or engineering efficiency of production. As such quantitative metrics of input, and sometimes output, are emphasized. Productivity is distinct from metrics of allocative efficiency, which take into account both the monetary value (price) of what is produced and the cost of inputs used, and also distinct from metrics of profitability, which address the difference between the revenues obtained from output and the expense associated with consumption of inputs (Pineda, 1990; Saari, 2006). Step 4

Calculate shareholder value (SV)

SV is the part of its capitalisation that is equity as opposed to long-term debt. In the case of only one type of stock, this would roughly be the number of outstanding shares times current share price. Things like dividends augment SV while issuing of shares (stock options) lower it. This SV added should be compared to average/required increase in value.

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SV is the value of the firm minus the future claims (debts). The value of company can be calculated as the net present value of all future cash/flows plus the value of the nonoperating assets of the company. So Shareholder value = Corporative value (firm value) − Future claims (debits) = (NPV of all future free cash flows + value of non-operating assets) − Future claims (debits)

Non-operating assets include marketable securities (stocks), excess real state, and over funded pension plans. Future claims (debits) include interest – bearing debts (long term and short term), capital lease obligations, underfunded pension plans, and contingent liabilities.

8

Conclusions

This paper explored the synergies resulting from the combination of state-of-the art quality initiatives, lean and DFSS, and develop an integrated SCOR with lean and DFSS methodologies for their applications to service process improvement and design/or resign. The integration model presented here provides a roadmap to the real-world application of DFSS and lean production methodologies in industrial circles, and it mat applied to any industrial circumstance to improve process, product, and service quality. The significant benefits of the integration model are its implementation roadmap, combination of techniques in every step and philosophy of management, as well as its development of the quality initiative in the process of continuous quality implementation. DFSS has to cover the full life cycle of any new products, right from the organisation’s agreement on development, to the stage of full commercial delivery of the product. Various DFSS methodologies like DMADV, define, measure, analyse, design, optimise, verify (DMADOV), define, customer concept, design and implement, (DCCDI), identify, design, optimise and validate (IDOV) and define, measure, explore, develop and implement (DMEDI). In this paper, we use DMADV methodology. In order to achieve the full potential of the integration model application, further research should focus on the impact of the application of this integration model to the realistic industry circumstances, and should explore an evaluation mechanism which would enable us to understand the priority for selecting the applicable industry section to carry the model.

Acknowledgements I would like to thank the anonymous reviewers for their constructive comments on this paper.

Reference Banuelas, R., Johnson, M., Virakul, T. and Antony, J. (2009) ‘Assessing the role of Six Sigma in a supply chain: an exploratory study in the UK manufacturing organizations’, International Journal of Six Sigma and Competitive Advantage, Vol. 5, No. 4, pp.380–397.

Developing a lean design for Six Sigma through supply chain methodology 433 Burton, T.T. (2001) Is this a Six Sigma, lean, or Kaizen Project?, Breakthrough, Bedford. Buss, P. and Ivey, N. (2001) ‘Dow chemical design for sigma rail delivery project’, Proceeding of the 2001 Winter Simulation, Conference, pp.1248–1251. Chang, C.M. and Su, C.T. (2007) ‘Service process design and/or redesign by fusing the powers of design for Six Sigma and lean’, Journal of Six Sigma and Competitive Advantage, Vol. 3, No. 2, pp.171–191. Chase, R.B., Aquilano, N.J. and Jacobs, R.F. (2000) Operations Management for Competitive Advantage, 9th ed., Chapter 10, McGraw Hill. Chowdhury, S. (2002) Design for Six Sigma: The Revolutionary Process for Achieving Extraordinary Profit, Kaplan Professional Company. Cronemyr, P. (2007) ‘DMAIC and DMADV – differences, similarities and synergies’, International Journal of Six Sigma and Competitive Advantage, Vol. 3, No. 3, pp.193–209. Deo, H. (2005) ‘Information technology SCOR, supply chain council, score-user seminar, manufacturing competitiveness: different systems to achieve the same results’, Production and Inventory Management Journal, Washington, DC., Vol. 4, No. 1, pp.56–65. Desai, D.A. (2008) ‘Improving productivity and profitability through Six Sigma: experience of a small-scale jobbing industry’, International Journal of Productivity and Quality Management, Vol. 3, No. 3, pp.290–310. Eckes, G. (2001) The Six Sigma Revolution, John Wiley & Sons, Chi Chester. Etienne, E.C. (2009) ‘The analysis and evaluation of quality system using the Six Sigma benchmark: evidence for the robustness of Six Sigma processes, International Journal of Productivity and Quality Management, Vol. 4, No. 2, pp.178–198. Fliedner, G. (2003) ‘CPFR: an emerging supply chain tool’, Industrial Management & Data System, Vol. 103, pp.14–21. George, M. (2003) lean Six Sigma for Service: How to Use lean Speed and Six Sigma Quality to Improve Service and Transaction, McGraw-Hill, New York. George, M.L. (2002) lean Six Sigma, The McGraw-Hill Companies, Inc. Gibbons, P.M. (2008) ‘Introducing a lean resource mapping framework’, Journal of Six Sigma and Competitive Advantage, Vol. 4, No. 4, pp.355–381. Grewal, C. (2008) ‘An initiative to implement lean manufacturing using value stream mapping in small company’, International Journal of Manufacturing Technology and Management, Vol. 15, Nos. 3/4, pp.404–417. Haik, B. and Roy, D. (2005) Service Design for Six Sigma, John Wiley & Sons, New York. Hines, P., Holweg, M. and Rich, N. (2004) ‘Learning to evolve, a review of contemporary lean thinking’, International Journal of Operations and Production Management, Vol. 24, No. 10, pp.994–1011. Jugulum, R., Kamarthi, S., Ibrahim, K. and Samuel, P. (2009) ‘Robust design of a radio-frequency identification systems using design for Six Sigma approach’, International Journal of Six Sigma and Competitive Advantage, Vol. 5, No. 1, pp.100–112. Kent, D. and Attri, H. (2007) SCOR, lean and Six Sigma Supply Chain Strategy available at http://www. eKnowtion.com (accessed on 10 April 2007). Knowles, G., Whicker, L., Femat, J.H. and Canales, F.D. (2005) ‘A conceptual model for the application of Six Sigma methodologies to supply chain improvement’, International Journal of Logistics: Research and Applications, Vol. 8, No. 1, pp.51–65. Lathin, D. and Mitchell, R. (2000), ‘lean manufacturing: techniques, people and culture’, Annual Quality Congress Proceedings, pp.321–325, Milwaukee. Lazreg, M. and Gien, D. (2009) ‘Integrating Six Sigma and maintenance excellence with QFD’, International Journal of Productivity and Quality Management, Vol. 4, Nos. 5/6, pp.676–690. Natarajan, R.N. and Morse, J. (2009) ‘Six Sigma in services – challenges and opportunities’, International Journal of Productivity and Quality Management, Vol. 4, Nos. 5/6, pp.658–675.

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Mazzola, M., Gentili, E. and Aggogeri, F. (2007) ‘SCOR, lean and Six Sigma integration for complete industrial improvement’, International Journal of Manufacturing Research, Vol. 2, No. 2, pp.188–197. Miller, D. (2005) Going lean in Healthcare, from Institute for Healthcare implement, available at http://wwwihi.org (accessed on 24 January 2010). Moore, R. (2000) ‘Management side of engineering: comparing major manufacturing improvement methods – part 2’, Plant Engineering, Vol. 55, No. 10, pp.22–26, Barrington. Nave, D. (2002) ‘How to compare Six Sigma lean and the theory of constraints’, Quality Progress, Vol. 35, No. 3., pp.73–78. Pineda, A. (1990) A Multiple Case Study Research to Determine and Respond to Management Information Need Using Total-Factor Productivity Measurement (TFPM), Virginia Polytechnic Institute and State University. Pyzdek, T. (2003) The Six Sigma Handbook: A Complete Guide for Green Belts, Black Belts and Managers at All Levels, McGraw-Hill Book Company, New York. Rate, S. (2002) Design for Six Sigma, Rate and Strong Publishers, Massachusetts. Revere, L., Kadipasaoglu, S.N. and Zalila, F. (2006) ‘An empirical investigation into Six Sigma critical success factors’, International Journal of Productivity and Quality Management, Vol. 1, No. 3, pp.224–252. Saari, S. (2006) Productivity, Theory and Measurement in Business, European Productivity Conference, Espoo, Finland. Sahin, F. (2000) ‘Manufacturing competitiveness: difference systems to achieve the same results’, Product and Inventory Manufacturing Journal, Vol. 41, No. 1, pp.56–65, Alexandria. Sanchez, A. and Perez, M. (2001) ‘lean indicators and manufacturing strategies’, International Journal of Operations and Production Management, Vol. 21, No. 1, pp.1433–1451. Smith, R. and Adams, E. (2001) ‘Lead Sigma: advanced quality’, Annual Quality Congress Proceedings, pp.369–379, Milwaukee. Snee, R.D. (2000) ‘Impact Six Sigma on quality engineering’, Quality Engineering, Vol. 12, No. 3, pp.9–14. Snee, R.D. and Hoerl, R.W. (2003) Leading Six Sigma, Chapter 7, pp.182–183, Prentices Hall. Su, C.T., Chiang, T.L. and Chang, C.M. (2006) ‘Improving service quality by capitalizing on an integrated lean Six Sigma methodology’, International Journal of Six Sigma and Competitive Advantage, Vol. 2, No. 1, pp.1–22. Thomas, M. and Singh, N. (2006) ‘Complexity reduction in product design and development using design for Six Sigma’, International Journal of Product Development, Vol. 3, Nos. 3/4, pp.319–336. VICS (2006) The 2006 VICS Collaborative Commerce Achievement Awards. Wang, F.K., Du, T.C. and Li, E.Y. (2004) ‘Applying Six Sigma to supplier development’, Total Quality Management, Vol. 15, Nos. 9/10, pp.1217–1229. Yang, K. and Cai, X. (2009) ‘The integration of DFSS, lean product development and lean knowledge management’, International Journal of Six Sigma and Competitive Advantage, Vol. 5, No. 1, pp.75–99.