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41.
42.
《Quality Engineering》2012,24(2):180-203
ABSTRACT This case study quantifies the trade-off between customer service and inventory in a multinode supply chain while assessing system performance. An integrated and generalized modeling framework is used that incorporates define, measure, analyze, improve, control (DMAIC) methodology and designed experiments. Many traditional models require normality in demand and supply, but this is often not representative of reality. Therefore, this study leverages discrete-event simulation to replicate and understand the variation in a real-world supply chain at a large multinational corporation. The goal of this modeling application is to provide dynamic decision support to facilitate effective supply chain design. The study uses an innovative three-stage analytical approach to study a multi-echelon distribution network. The first stage uses DMAIC to highlight areas of variability in the process, enabling identification of key high-risk inputs affecting system performance. The next stage, discrete-event simulation, utilizes DMAIC results in the development of a validated model that represents the real-world variability present in the supply chain. The third and final stage, designed experiments, is used to analyze the simulation output and quantify the factors that drive supply chain performance, specifically inventory levels and customer service (fill rate) at various stages of the supply chain. To more effectively respond to stochastic behavior of customers, study results impact decision making and facilitate inventory replenishment policy changes. The analysis also helped in the proper allocation of resources to manage the various stock-keeping units (SKU) classes and customer categories. This proactive modeling approach is robust and readily replicated in any supply chain. 相似文献
43.
《Quality Engineering》2012,24(4):431-442
This article presents an application of the “Six Sigma” DMAIC model to G.E.P. Box's famous “paper helicopter” experiment. The Improve and Control Phases are presented here. The Define, Measure, and Analyze Phases were presented in an earlier paper. The intent of this article is to present the reader with a case study for structuring a “Six Sigma” project. 相似文献
44.
《Quality Engineering》2012,24(2):113-124
ABSTRACT Health care today is facing serious problems: quality of care does not meet patients' needs and costs are exploding. In the cardiology department of the Virga Jesse Hospital in Belgium, discharged patients are advised to participate in a rehabilitation program. However, many of the discharged patients do not join the program, and others quit before being declared cured (a so-called dropout). An improvement project was started that aims to increase revenues by either attracting more patients to the rehabilitation program or reducing the fraction of dropouts. A large data set with 516 treated patients was available. We model the probability that a patient joins the program as a function of various numerical and categorical influence factors. First an exploratory data analysis is performed, using bar charts and box plots. This is followed by a more formal statistical analysis using logistic regression. The logistic regression model reveals the important influence factors. The probability of joining the program depends on whether a patient has a car at his or her disposal and the distance from a patient's home to the hospital. As a solution, various measures to stimulate carpooling were implemented. Prior to the implementation, a cost–benefit analysis was conducted using the fitted regression model. 相似文献
45.
《Quality Engineering》2012,24(4):552-557
ABSTRACT This is the fourth article in a series reviewing statistical standards published under the auspices of the International Organization for Standardization Technical Committee 69 on Applications of Statistical Methods. Here the emphasis is on the technical guidelines and standards published or under development by the relatively new subcommittee SC-7, Applications of Statistical and Related Techniques for the Implementation of Six Sigma. The creation of this subcommittee is reviewed and its early successes are highlighted. 相似文献
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面对越来越大的挑战和压力,为了帮助企业赢得竞争,更有效地推进工业工程改善和精益生产已成为提升企业竞争力的关键要素。本文运用质量管理学中的方式方法,采取DMAIC办法论,QC7大手法和统计学的分析方法,以及工序能力分析等理论和实践方法对生产实践进行项目改善,最终实现产能提升,效益最大化的目标。 相似文献
48.
Andrej Trnka 《通讯和计算机》2013,(8):1063-1069
Six Sigma is a rigorous, focused, and highly effective implementation of proven quality principles and techniques. A company＇s performance is measured by the sigma level of their business processes. Traditionally companies accepted three or four sigma performance levels as the norm. The Six Sigma standard of 3.4 problems-per-million opportunities is a response to the increasing expectations of customers. DMAIC is an acronym for five phases of Six Sigma methodology： Define, Measure, Analyze, Improve, Control. This paper describes possibility of using Bayesian Network for retraining data mining model. Concrete application of this proposal is in the field of the chum. Chum is a derivation from change and turn. It can be defined as a discontinuation of a contract. Data mining methods and algorithms can predict behavior of customers. We can get better results using Six Sigma methodology. The goal of this paper is proposal of implementation chum （with Bayesian network） to the phases of Six Sigma methodology. 相似文献
49.
《Measurement》2016
Measurement error is an unavoidable source of variation in any decision-making process based on experimental research. Components of variation due to measurement system and manufacturing process must be estimated and special causes of variation should be reduced whenever possible. GR&R (gage repeatability and reproducibility) studies quantify these sources of variation by using analysis of variance. The main contribution of this paper is to conjoin GR&R and the multiple comparisons method of Scott-Knott in order to help practitioners identifying special causes of variation in empirical studies. Stainless steel cladding process has been evaluated to validate the proposed procedure. The experimental findings have shown that the well-structured method based on Scott-Knott test was effective in indicating the source of error due to reproducibility. 相似文献
50.
为了辅助软件组织有效实施根本原因分析过程,结合CMMI中CAR过程域的要求以及6sigma中DMAIC 思想,提出了一种PAIE (Plan-Analyze-Implement-Evaluate)过程框架,清晰地阐述了原因分析过程的基本方法和步骤.通过在实际软件项目过程中的应用证明,使用PAIE过程框架能够快速、准确地定位问题并找到根本解决方法,有效地提高了原因分析过程的系统性与效用. 相似文献