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.     

The construction and application of Six Sigma quality indices

Process quality is the primary factor in facilitating product sales. In accordance with the concept of Six Sigma, numerous studies have employed process capability indices for the determination of process quality levels. Unfortunately, existing indices present only a range of quality levels rather than a specific quality level value. This paper aims to propose Six Sigma quality indices for the assessment of quality levels associated with unilateral as well as bilateral specifications. To ensure the reliability in process assessment, we employ the lower confidence limit of the indices to serve as a standard and develop a process quality analysis chart for the simultaneous evaluation of larger-the-better, smaller-the-better and nominal-the-best quality characteristics with the aim of identifying the causes of sub-standard quality. The resulting chart also provides a valuable reference by which to guide efforts aimed at improvement. Finally, we present three cases and numerical experiments to demonstrate the practical applicability of the proposed method.     

精益六西格玛改进服务流程的实证分析

精益六西格玛通过收集客户之声、界定、测量、分析、改进和控制进行服务流程改进,深层挖掘银行业务的潜力,减少浪费。以A银行在营业网点的汇款业务为例,通过数据的采集以及分析,运用科学的改进工具,使得汇款业务流程进一步优化,业务操作时间减少,提高了银行顾客满意度,减小业务员的工作强度。     

对6Sigma范式的改进

6Sigma作为质量改进的一种体系,自从10多年前被提出以来,在工业界得到了越来越多的关注和认同。目前,制造和服务这两种类型运作的质量水平,都可以用“Sigma水平”来进行标定;也有不少公司开始纷纷以“6Sigma组织”的称号自我标榜。本文通过考察6Sigma的基础及其长期潜能,以一种现实的观点对6Sigma体系进行了评述;并阐明了在21世纪动荡的工商业环境中,一个有远见的组织,其目标应该超越6Sigma的基准。文中提出,为了强化常规的6Sigma方法,必须按照更高的要求,实现一种“8S”范式,以保证持续的卓越质量水平。     

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.     

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.     

Context-Based Statistical Process Control

Most statistical process control (SPC) methods are not suitable for monitoring nonlinear and state-dependent processes. This article introduces the context-based SPC (CSPC) methodology for state-dependent data generated by a finite-memory source. The key idea of the CSPC is to monitor the statistical attributes of a process by comparing two context trees at any monitoring period of time. The first is a reference tree that represents the “in control” reference behavior of the process; the second is a monitored tree, generated periodically from a sample of sequenced observations, that represents the behavior of the process at that period. The Kullback–Leibler (KL) statistic is used to measure the relative “distance” between these two trees, and an analytic distribution of this statistic is derived. Monitoring the KL statistic indicates whether there has been any significant change in the process that requires intervention. An example of buffer-level monitoring in a production system demonstrates the viability of the new method with respect to conventional methods.     

基于小批量多品种生产环境的统计过程质量控制研究

分析了先进制造技术环境下实施统计过程质量控制所存在的问题,给出了一种基于正态过程的改进的标准化控制图,适用于小批量多品种生产环境下对过程均值、过程方差的有效控制。     

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．     

Probability Constrained Optimization as a Tool for Functional Design for Six Sigma

An important up-stream activity in the overall design of a system is the so-called functional design wherein the means and tolerances of the design variables are determined with respect to the competing demands of quality and cost. In this article probability constrained optimization is invoked to produce a functional design that focuses on the goal of design for Six Sigma (i.e., improved customer satisfaction, robustness, and predictable cost levels). Herein, a maximum system probability of nonconformance is obtained from a prescribed defect rate that in turn provides the primary design constraint. The production cost provides the objective function to be minimized in order to allocate the design parameters. All three quality metrics (e.g., target/larger/smaller-is-best) and robustness are inherent in the approach. The design of an electro-mechanical servo system serves as a case study wherein three responses are related to three control variables and two noise variables by mechanistic models. Designs for selected defect rates show the practicality and potential of the approach.     

面向小批量生产的统计过程控制的研究

指出了在小批量生产环境下实施统计过程控制存在的问题,用概率积分变换理论,给出了控制过程均值、过程方差的标准化控制图,适用于小批量生产环境下对过程均值、过程方差的有效控制。     

DMAIC流程在AC-pin铆接质量改进中的应用

通过对C企业AC-pin铆接过程系统实施六西格玛DMAIC流程来提高AC-pin铆接质量。首先,对问题进行定义,明确项目的改进范围和改进目标。接着,分析AC-pin铆接过程的主要缺陷类型,并对相关测量系统进行评价与改进。在此基础上,进一步分析导致AC-pin铆接缺陷的根本原因,并确定相应的改进方案,使AC-pin铆接缺陷由先前的7000ppm降到500ppm以下,同时产量得到显著提高。最后,对关键质量特性建立相应的控制方案和纠偏措施,以使改进成果得以保持。DMAIC流程在AC-pin铆接质量改进中的成功应用有助于促进六西格玛管理在我国企业的有效实施,提升企业的质量管理水平。     

Using Factor Effects Analysis to Improve Statistical Process Control

Quality practitioners are taught that when a control chart shows an out-of-control condition they should take corrective action but not what action. This paper fills a gap because it provides a method of identifying the significant contributors thus providing a guide as to what to do.     

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.     

多品种小批量生产的SPC应用研究

综述了多品种小批量生产方式的特点以及该生产方式下SPC(统计过程控制)的应用现状,指出常规控制图不适用于多品种小批量生产的问题,提出结合通用控制图、累积和(Cumulative-Sum,CUSUM)控制图和指数加权移动平均(Exponentially Weighted Moving-Averages,EWMA)控制图的解决方法,并总结出该SPC方法用于处理多品种小批量生产中微小偏差的步骤。     

统计过程控制在微电脑控制器生产中的应用:案例研究

以某电子集团生产的某类型控制器的实际生产为例,采用因果分析法对其生产过程中造成质量缺陷的原因从5M1E(人、机、料、法、测、环)方面进行综合分析.通过对其测量系统进行监控,在其稳定可靠的情况下采集数据.运用SPC技术对波峰焊工序进行控制图监控,对失控原因进行分析并在线调整.有效地保证了控制器的质量,为其质量改善指明了方向.