Quality evaluation of internal cylindrical grinding process with multiple quality characteristics for gear products

Gears are among the most crucial components in the transmission systems of machine tools. Gear manufacturing includes a number of processing procedures. The grinding process is an important procedure involving high precision and fairly small grinding surfaces. For this reason, this study aimed at developing a quality assessment model for the internal cylindrical grinding process of gears. The Six Sigma quality indices (SSQIs) were used to directly assess the quality of the internal cylindrical grinding process due to their ability to directly reflect quality level and process yield. Since the process may include nominal-the-best (NTB), larger-the-better (LTB) and smaller-the-better (STB) quality characteristics, so we used the variable transformation method to normalise the specifications of each quality characteristic for the convenient and effective management and analysis of process performance for multiple quality characteristics. We then constructed a multi-characteristic process quality analysis chart (MPQAC) to simultaneously assess the quality levels of various quality characteristics. Furthermore, the MPQAC can provide references for process improvement. This ensures the quality of internal cylindrical grinding and enhances the quality of gear and machine tool products. Finally, a real-world application and numerical experiments demonstrate the effectiveness and practical applicability of the proposed method.     

Testing and analysing capability performance for products with multiple characteristics

Process capability analysis is a vital part of an overall quality improvement programme. Numerous techniques and tools have been proposed for process capability analysis. Among these, indices and charts of process capability are simple and effective tools and widely used in the manufacturing industry. Many scholars have revealed numerous valuable aspects of previously developed tools and methods. Due to the rising demands of product quality, the current tools and methods are insufficient for enabling managers to make informed decisions. To address this gap, this study proposes a hypothesis testing procedure which determines whether the process capabilities satisfy the target level. Furthermore, this study proposes an integrated quality test chart (IQTC), which can display the process potential and performance for an entire product with smaller-the-better, larger-the-better and nominal-the-best specifications. The proposed procedure and IQTC incorporate the quality-level concept of the Six Sigma model and can be used to quantitate the relationships among the quality level, capability indices and process yield. They can be applied to assist managers in measuring, monitoring, analysing and improving process performance in a timely manner which will help ensure that the quality levels of their products meet customer demands. Finally, an example is provided to illustrate how to use the proposed procedure and IQTC.     

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.     

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 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.     

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.     

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.     

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.     

Two-phase selection framework that considers production costs of suppliers and quality requirements of buyers

Buyers are faced with selecting the optimal supplier, while suppliers are left to consider production costs. In this study, we developed a two-phase selection framework that allows buyers to evaluate the performance of suppliers while taking production costs into account for value maximisation. This scheme is a win-win solution capable of promoting long-term relationships between buyers and suppliers. Under the assumption of normality, the first phase involves constructing a new Six Sigma quality capability analysis chart (SSQCAC) which takes production costs into account. The objective is to evaluate all potential suppliers using the 100?×?(1–α)% upper confidence limit (UCL) of an integrated Six Sigma quality index (SSQI) Q_PIh when dealing with products with smaller-the-better (STB), larger-the-better (LTB), or nominal-the-best (NTB) quality characteristics. According to interval estimation theory, this method can have a significant impact on the consumption of resources; i.e. the production costs of the supplier can be decreased by reducing the production quality to below that required by the buyer. The proposed method also filters out unsuitable suppliers in order to simplify the decision problem and reduce computational demands and operational risks/costs without compromising the quality of the final product. In the second phase, a detailed analysis is conducted using Euclidean distance measure to select the optimal supplier from among the remaining candidates. We conducted a real-world case study to evaluate the efficacy of the proposed method. We also conducted comparisons with existing methods to demonstrate the advantages of the proposed method and its managerial implications. Suggestions for future study are also provided.     

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.     

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.     

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.     

装备维修辅助过程质量改进中的参数确定与测量分析

针对装备维修存在消耗大、效益小、污染重、环保轻的问题,基于"大质量观",文章运用六西格玛管理(Six Sigma Management,SSM)研究装备维修辅助过程的质量改进.介绍了SSM的基本思想,界定了装备维修辅助过程的概念和内涵;运用质量功能展开将装备维修辅助过程质量要求转化成可供测量的过程质量参数,并从重复性和再现性两个方面进行了测量系统分析,验证了测量系统的精确性.     

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.     

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.     

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.     

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.     

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.     

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.