Winning customer loyalty in an automotive company through Six Sigma: a case study

Six Sigma is a disciplined approach to improving product, process and service quality. Since its inception at Motorola in the mid 1980s Six Sigma has evolved significantly and continues to expand to improve process performance, enhance business profitability and increase customer satisfaction. This paper presents an extensive literature review based on the experiences of both academics and practitioners on Six Sigma, followed by the application of the Define, Measure, Analyse, Improve, Control (DMAIC) problem‐solving methodology to identify the parameters causing casting defects and to control these parameters. The results of the study are based on the application of tools and techniques in the DMAIC methodology, i.e. Pareto Analysis, Measurement System Analysis, Regression Analysis and Design of Experiment. The results of the study show that the application of the Six Sigma methodology reduced casting defects and increased the process capability of the process from 0.49 to 1.28. The application of DMAIC has resulted in a significant financial impact (over U.S. $110 000 per annum) on the bottom‐line of the company. Copyright © 2006 John Wiley & Sons, Ltd.     

An Application of Six Sigma to Reduce Waste

Six Sigma has been considered a powerful business strategy that employs a well‐structured continuous improvement methodology to reduce process variability and drive out waste within the business processes using effective application of statistical tools and techniques. Although there is a wider acceptance of Six Sigma in many organizations today, there appears to be virtually no in‐depth case study of Six Sigma in the existing literature. This involves how the Six Sigma methodology has been used, how Six Sigma tools and techniques have been applied and how the benefits have been generated. This paper presents a case study illustrating the effective use of Six Sigma to reduce waste in a coating process. It describes in detail how the project was selected and how the Six Sigma methodology was applied. It also shows how various tools and techniques within the Six Sigma methodology have been employed to achieve substantial financial benefits. Copyright © 2005 John Wiley & Sons, Ltd.     

Paper Organizers International: A Fictitious Six Sigma Green Belt Case Study. II

The purpose of this paper is to present the second part of a detailed, step-by-step case study of a simple Six Sigma Green Belt project. In the last edition of Quality Engineering, the first part of a Six Sigma Green Belt case study was presented. That paper showed the Define and Measure phases of the DMAIC method. This paper presents the rest of the case study, or the Analyze, Improve, and Control phases of the DMAIC method.     

Statistical Control of a Six Sigma Process

Six Sigma as a methodology for quality improvement is often presented and deployed in terms of the dpmo metric, i.e., defects per million opportunities. As the sigma level of a process improves beyond three, practical interpretation problems could arise when conventional Shewhart control charts are applied during the Control phase of the define-measure-analyze-improve-control framework. In this article, some alternative techniques are described for the monitoring and control of a process that has been successfully improved; the techniques are particularly useful to Six Sigma Black Belts in dealing with high-quality processes. The approach used would thus ensure a smooth transition from a low-sigma process management to maintenance of a high-sigma performance in the closing phase of a Six Sigma project.     

Paper Organizers International: A Fictitious Six Sigma Green Belt Case Study. I

“Six Sigma” management is in vogue in many of the world's largest and most successful corporations. However, for all of its popularity, there is much confusion as to the exact structure of a Six Sigma project. The purpose of this article is to present the first part of a detailed, step-by-step case study of a simple Six Sigma Green Belt project. This part of the case study presents the Define and Measure phases of the define-measure-analyze-improve-control (DMAIC) method for improving a process.     

Evaluating Six Sigma failure rate for inverse Gaussian cycle times

Six Sigma is a quality philosophy and methodology that aims to achieve operational excellence and delighted customers. The cost of poor quality depends on the sigma quality level and its corresponding failure rate. Six Sigma provides a well-defined target of 3.4 defects per million. This failure rate is commonly evaluated under the assumption that the process is normally distributed and its specifications are two-sided. However, these assumptions may lead to implementation of quality-improvement strategies that are based on inaccurate evaluations of quality costs and profits. This paper defines the relationship between failure rate and sigma quality level for inverse Gaussian processes. The inverse Gaussian distribution has considerable applications in describing cycle times, product life, employee service times, and so on. We show that for these processes attaining Six Sigma target failure rate requires higher quality efforts than for normal processes. A generic model is presented to characterise cycle times in manufacturing systems. In this model, the asymptotic production is described by a drifted Brownian motion, and the cycle time is evaluated by using the first passage time theory of a Wiener process to a boundary. The proposed method estimates the right efforts required to reach Six Sigma goals.     

A new model to implement Six Sigma in small- and medium-sized enterprises

The Six Sigma approach improves the quality of products in order to ensure customers’ satisfaction. This approach has yielded to interesting results for large enterprises. However, its implementation remains difficult for small- and medium-sized enterprises (SME). In fact, the use of the same tools is insufficient to achieve the objectives when considering financial constraints and the lack of data. The regular tools are complex for SMEs which require an adapted model to implement the approach successfully. In this paper, we propose a new model having the objective to facilitate the integration of Six Sigma in SMEs by avoiding the use of Black Belts, optimising the implementation costs and period, simplifying the Six Sigma structure and enhancing the communication between staff and managers. The model includes two imbricated loops: the first offers immediate improvement actions by estimating the capability and the stability of the process, while the second provides profound improvement actions using the fuzzy logic system and the analytic hierarchical process (AHP) method. An example illustrates the application of the proposed model in an SME.     

Implementing Evaluation of the Measurement Process in an Automotive Manufacturer: a Case Study

Reducing process variability is presently an area of much interest in manufacturing organizations. Programmes such as Six Sigma robustly link the financial performance of the organization to the degree of variability present in the processes and products of the organization. Data, and hence measurement processes, play an important part in driving such programmes and in making key manufacturing decisions. In many organizations, however, little thought is given to the quality of the data generated by such measurement processes. By using potentially flawed data in making fundamental manufacturing decisions, the quality of the decision‐making process is undermined and, potentially, significant costs are incurred. Research in this area is sparse and has concentrated on the technicalities of the methodologies available to assess measurement process capability. Little work has been done on how to operationalize such activities to give maximum benefit. From the perspective of one automotive company, this paper briefly reviews the approaches presently available to assess the quality of data and develops a practical approach, which is based on an existing technical methodology and incorporates simple continuous improvement tools within a framework which facilitates appropriate improvement actions for each process assessed. A case study demonstrates the framework and shows it to be sound, generalizable and highly supportive of continuous improvement goals. Copyright © 2003 John Wiley & Sons, Ltd.     

Six sigma-based approach to optimize deep drawing operation variables

The six sigma approach has been increasingly adopted worldwide in the manufacturing sector in order to enhance the productivity and quality performance and to make the process robust to quality variations. This paper deals with one such application of six sigma methodology to improve the yield of deep drawing operations. The deep drawing operation has found extensive application in producing automotive components and many household items. The main issue of concern of the deep drawn products involves different critical process parameters and governing responses, which influences the yield of the operation. The effects of these parameters are analysed by the DMAIC (Define, Measurement, Analyse, Improve, Control)-based six sigma approach. A multiple response optimization model is formulated using the fuzzy-rule-based system. The functional relationship between the process variables and the responses is established, and thereafter their optimum setting is explored with the aid of response surface methodology (RSM). Rigorous experimentations have been carried out, and it is observed that the process capability of processes is enhanced significantly, after the successful deployment of the six sigma methodology.     

Future‐Proofing Six Sigma

Six Sigma started some three decades ago as a problem solving framework for quality improvement. It has since evolved, while being implemented in industry, into a management approach to performance excellence. Whether Six Sigma will continue to enjoy the attention it has been getting and keep embraced by practitioners depends on whether its implementation continues to be in line with new organizational needs in the twenty‐first century. This paper considers what it would take for Six Sigma to face the future world and analyzes from both strategic and operational directions a number of maneuvers necessary to sustain its relevance. Various inclusive and proactive features are explained for remaking of a Six Sigma that is to remain in demand for many years to come. Copyright © 2013 John Wiley & Sons, Ltd.     

Integration of PCA and DEA for identifying and improving the impact of Six Sigma implementation on job characteristics in an automotive industry

This study presents an integrated approach, based on data envelopment analysis (DEA) and principal component analysis (PCA) methods, to evaluate the influence of Six Sigma deployment on key job characteristics in an automotive industry. The job characteristics are defined as satisfaction, stress, and security. A standard questionnaire is designed and distributed among the employees at the company's production site, who were affected by the implementation of Six Sigma. DEA and PCA methods are applied to measure the performance of the sub-groups of employees in the company. Consequently, the most efficient and inefficient sub-groups are determined. According to the findings of this investigation, it was perceived that the implementation of Six Sigma has had the greatest impact on job satisfaction. Additionally, a design of experiment was carried out to recognize the most effective job factor, which was identified to be the overall working conditions for the related case study. This is the first study that integrates DEA and PCA toward identifying and optimizing job characteristics in terms of Six Sigma implementation. The approach, employed in this study, can be easily used in the other manufacturing systems, in order to assist them to identify and improve their key job characteristics.     

A strategic assessment of six sigma

Six Sigma as a quality improvement framework has been gaining considerable attention in recent years. The hyperbole that often accompanied the presentation and adoption of Six Sigma in industry could lead to unrealistic expectations as to what Six Sigma is truly capable of achieving. In this paper, some strategic perspectives on the subject are presented, highlighting the potential and possible limitations of Six Sigma applications particularly in a knowledge‐based environment. Without delving into the mechanics of the subject in detail, the points raised could be useful to those deliberating on the appropriateness of Six Sigma to their respective organizations. Copyright © 2002 John Wiley & Sons, Ltd.     

Six Sigma in industry: some observations after twenty‐five years

Six Sigma has enjoyed considerable popularity in the industry for about a quarter of a century. While the standard contents of Six Sigma have been described and discussed widely, some little articulated aspects of Six Sigma implementation deserve the attention of serious practitioners. In this paper, a ‘5W+1H’ (What, Why, When Where, Who, How) format is used to elucidate the nature of Six Sigma in a non‐mathematical discussion, followed by observations peculiar to the usual mode of development of Six Sigma professionals. It is pointed out that Six Sigma has Statistical Thinking as its foundation; for Six Sigma and its associated frameworks such as Design for Six Sigma and Lean Six Sigma to continue to be effective, it is important that users have a clear understanding of the nature of Six Sigma and be able to address the related challenges in practice. Copyright © 2010 John Wiley & Sons, Ltd.     

A framework for the integration of Green and Lean Six Sigma for superior sustainability performance

Evidence suggests that Lean, Six Sigma and Green approaches make a positive contribution to the economic, social and environmental (i.e. sustainability) performance of organisations. However, evidence also suggests that organisations have found their integration and implementation challenging. The purpose of this research is therefore to present a framework that methodically guides companies through a five stages and sixteen steps process to effectively integrate and implement the Green, Lean and Six Sigma approaches to improve their sustainability performance. To achieve this, a critical review of the existing literature in the subject area was conducted to build a research gap, and subsequently develop the methodological framework proposed. The paper presents the results from the application of the proposed framework in four organisations with different sizes and operating in a diverse range of industries. The results showed that the integration of Lean Six Sigma and Green helped the organisations to averagely reduce their resources consumption from 20 to 40% and minimise the cost of energy and mass streams by 7–12%. The application of the framework should be gradual, the companies should assess their weaknesses and strengths, set priorities, and identify goals for successful implementation. This paper is one of the very first researches that presents a framework to integrate Green and Lean Six Sigma at a factory level, and hence offers the potential to be expanded to multiple factories or even supply chains.     

Improving Process Capability of Manufacturing Process by Application of Statistical Techniques

This article describes the application of statistical techniques in solving a problem of high rejection and rework due to variation in the machining process. The rejections in the shop floor of a company were studied through Pareto analysis for prioritizing the problems due to different sources. The grinding process was found to be the most contributing among all the processes towards rejection and rework. The process capability of this grinding process was evaluated and found to be very low. A step by step method was adopted by the application of several statistical techniques such as design of experiments for solving this problem. As a result of the study, the process capability has improved drastically. This has lead to reduction in the problems due to high rejection and rework in shop floor.     

Reducing Patient Waiting Time in Outpatient Department Using Lean Six Sigma Methodology

This article addresses the issue of longer patient waiting time in the outpatient department (OPD) of a super specialty hospital attached to a manufacturing company in India. Due to longer waiting times at OPD, employees need to be away from the workplace for a longer duration. This problem was addressed through the Lean Six Sigma (LSS) methodology. The process, starting from registration of a patient to dispensing of medicine, was included in the project. The non‐value added steps in the process were identified, and actions were initiated. A cause and effect diagram was prepared for high patient waiting time, and causes were validated with the help of data collected from the process. Statistical tools such as Kruskal–Wallis test, Box – Cox transformation, Control charts, normality test, etc., were used within the LSS methodology not only to identify the causes but also to sustain the improvements. As a result of this project, the average waiting time reduced from 57 min to 24.5 min and the standard deviation was reduced to 9.27 from 31.15 min. This will help the hospital to serve patients better and faster, which, in turn, will lead to a reduction in delay of treatment and a faster recovery of patients. The productivity loss due to absenteeism of employees from the workplace could be reduced. Generally, in an Indian health care scenario, most of the activities were dependent on individual doctors rather than processes. This project has helped the clinicians and the hospital management to identify the weak areas in the process for improvement. Because of the implemented solutions, understanding the history of past treatments and medications of the patients was easy for the doctors. Also, the practical validity of deploying LSS in a healthcare scenario was justified with this study. Copyright © 2013 John Wiley & Sons, Ltd.     

六西格玛在广州市规划局IT运维服务质量管理中的应用

论文总结了目前广州市规划局IT运维服务工作中存在的一些问题,介绍了使用六西格玛管理方法测量IT运维服务流程、发现服务流程缺陷、改善服务质量,指出六西格玛管理方法与IT服务管理密切结合是提高用户满意度的有效方法。     

On the evaluation of Six Sigma projects

Most of the research on the success in implementing Six Sigma agrees upon the fact that one of the key success factors is the selection of profitable projects. This seems to be especially important for high‐risk, large‐scope and long‐term projects, as is mostly the case in the design for Six Sigma projects. The purpose of this paper is to outline Six Sigma project characteristics and to present a new model for evaluating Six Sigma projects. To design a Six Sigma project evaluation model, we utilized mathematical optimization modeling techniques and real options theory. The model allows for the quantification of not only the project's value prior to its start but also its progress and the consideration of possible decisions based on this progress. Copyright © 2009 John Wiley & Sons, Ltd.     

Measuring Six Sigma Project Effectiveness using Fuzzy Approach

Six Sigma methodology for process improvement is being used by industries to improve customer satisfaction, business results or both. The success of Six Sigma implementation can be measured by evaluating the effectiveness of the completed projects. The other objective of project effectiveness measurement scheme is to keep the team focused and motivated. A good measurement system should be able to measure and compare projects of various types and need, including benefits from the projects. The project effectiveness measurement scheme should include success factors like project selection, involvement of management, results achieved, conduct of the project and monitoring and review of the project. A Six Sigma project effectiveness evaluation system is generally based on the perception of people that can result in unreliable measurement. To overcome this deficiency, we used a fuzzy approach based on linguistic variables and fuzzy numbers for measuring the project effectiveness in this study by using the perception of management. Two methods for measuring effectiveness of selected sample projects are suggested. The outcome from this research would be helpful for the practicing industries to use this methodology for an unbiased evaluation of completed projects. Copyright © 2012 John Wiley & Sons, Ltd.