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.     

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.     

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.     

Six Sigma Literature: A Review and Agenda for Future Research

Like quality management in general, Six Sigma has penetrated into most sectors of today's business world. Although Six Sigma originated in industry, it has inspired a considerable amount of academic literature. This paper reviews this literature describing the trends, sources, and findings. The paper also seeks to synthesize the literature, with an emphasis on establishing its relationship to quality management theory and topics for future research. In doing so, there is an attempt to answer the following fundamental questions. (i) What is Six Sigma? (ii) What are its impacts on operational performance? (iii) What roles can academics usefully play in relation to Six Sigma? Copyright © 2006 John Wiley & Sons, Ltd.     

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.     

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.     

Statistical Reason for the 1.5σ Shift

Ever since Motorola, Inc. introduced its Six Sigma quality initiative, quality practitioners have questioned why followers of this philosophy add a 1.5σ shift to the average before estimating process capability. Six Sigma advocates claim such an adjustment is necessary but offer only empirical studies as justification for this decision. By examining the sensitivity of control charts to detect changes of various magnitudes, this article provides a statistically based reason for including such a shift in the process average. A new capability index, called dynamic C_pk, incorporating this shift is introduced.     

The Role of Statistical Design of Experiments in Six Sigma: Perspectives of a Practitioner

Six Sigma has now been well recognized as an effective means of attaining excellence in the quality of products and services. It entails the use of statistical thinking as well as management and operational tools to bring about fundamental improvements. This article explains, in a nonmathematical language, the rationale and mechanics of design of experiments as seen in its deployment in Six Sigma. It also outlines the way in which the design of experiments has been utilized in the past for quality improvement, culminating in its important role in Six Sigma. An appreciation of the changing scope of experimental design applications over the years and in the future would provide useful perspectives on the significance of Six Sigma in an organization's quest for quality excellence.     

Six Sigma experience as a stochastic process

This study empirically investigates the states of Six Sigma from a stochastic point of view. By the means of an advanced survey, 97 respondents are asked to rate the effect of Six Sigma on different performance categories, the cost of implementing Six Sigma, the level of enthusiasm and expectations from Six Sigma over 20 years. The autocorrelation and cross-correlation functions of these processes are analyzed to investigate the stages of Six Sigma. Consequently, new concepts namely steady state of Six Sigma and Six Sigma experience functions are introduced which shed light on the life cycle of Six Sigma within the companies.     

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.     

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。     

Six Sigma企业与品质管理系统在制膜工业上的应用

六西格玛作为一种有效的企业和品质管理系统,已被许多美国大公司采用．将六西格玛用于制膜工业,可以使膜产品具有更强的市场竞争力．文章通过一些实例,介绍了六西格玛在科研和制膜方面的应用．     

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.     

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.     

Management of Parametric Response in Design of Experiments

Routine applications of design of experiments (DOE) by non‐mathematicians assume that each response value is static in nature, i.e. with an expected value that is constant for a given set of input factor settings. When this assumption is not valid, it is important to capture the dynamic characteristics of the response for effective process or system characterization, monitoring, and control. With the purpose of recognizing the self‐changing nature of the response owing to factors other than those built into the DOE, thereby gaining a better ability to shape the behavior of the response, this paper describes the reasoning and procedure needed for such ‘parametric responses’, via common techniques of mathematical modeling and optimization. The procedure is intuitive but essential and useful in DOE studies as these become increasingly popular by practitioners in the context of improvement projects such as those related to Six Sigma or stand‐alone performance optimization initiatives. Copyright © 2013 John Wiley & Sons, Ltd.     

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.     

Application of six sigma methodology to reduce defects of a grinding process

Six Sigma is a data‐driven leadership approach using specific tools and methodologies that lead to fact‐based decision making. This paper deals with the application of the Six Sigma methodology in reducing defects in a fine grinding process of an automotive company in India. The DMAIC (Define–Measure–Analyse–Improve–Control) approach has been followed here to solve the underlying problem of reducing process variation and improving the process yield. This paper explores how a manufacturing process can use a systematic methodology to move towards world‐class quality level. The application of the Six Sigma methodology resulted in reduction of defects in the fine grinding process from 16.6 to 1.19%. The DMAIC methodology has had a significant financial impact on the profitability of the company in terms of reduction in scrap cost, man‐hour saving on rework and increased output. A saving of approximately US$2.4 million per annum was reported from this project. Copyright © 2011 John Wiley & Sons, Ltd.     

精益六西格玛理论研究与应用综述

精益六西格玛(Lean Six Sigma, LSS)作为持续改进与创新的有力工具,在业界(制造业、建筑业、服务业甚至非盈利性组织)得到广泛的应用,但学术界和产业界对LSS的认识和理解仍存在一些差异。为了构建对LSS更为全面的认识,基于Web of Science 数据库中题目含有“六西格玛”或“精益六西格玛”的2701篇文献分析,简要回顾LSS的起源,系统梳理LSS在理论研究和产业界应用的现状,给出6个主要的研究内容。结合LSS在中国的应用实践,并从战略、系统和集成3个角度展望LSS的未来发展趋势,期望对精益六西格玛的学术研究和产业应用提供指导和参考。     

Lean,Six Sigma and Lean Six Sigma: an analysis based on operations strategy

There is a growing need for operations management models that contribute to the continuous improvement of company processes, among them we highlight lean manufacturing, Six Sigma and, more recently, Lean Six Sigma (LSS). This article aims (1) to identify and analyse the differences and complementarities in the production decision areas for each one of the three models; (2) to identify the competitive priorities that lead to the best performance as a result of policies followed in the decision areas as a result of the adopted model. First, a theoretical conceptual model was developed based on a review of the literature, followed by a exploratory research questions applied to manufacturing companies that use the lean, Six Sigma or LSS manufacturing models in southern Brazil. The main results show that there are differences in the models in relation to the importance of the decision areas and the performance achieved in the competitive priorities. Individually, lean manufacturing, Six Sigma and LSS have varying degrees of importance in the Facilities, Vertical Integration and Production Planning and Control decision areas. The performance dimensions with the best performance are speed, quality, reliability and cost.