过程监控的电源指南

IF 1.3 4区 工程技术 Q4 ENGINEERING, INDUSTRIAL
Darwin J. Davis, James M. Lucas, E. Saniga, Michael S. Saccucci
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引用次数: 0

摘要

摘要我们提出了一个设计监控程序的过程,其中包括实用的权力指南。这些指导原则以平均跑步长度(ARL)为基础。具体的指导指标是控制中的ARL(ARLic)与失控的ARL的比率(ARLoc)。我们推荐的设计过程使用ARL比率,结合ARLic、ARLoc和ARL曲线,设计有效的过程监控程序。为了获得足够的功率,我们通常建议ARL比率为20或更高,并认为通常应避免ARL比率小于10的监测程序。ARL比率介于10和20之间是一个值得注意的领域,这使我们能够提出一个用于监控程序设计的红绿灯类型模型。我们还讨论了这些指南的例外情况,以及在控制图设计的其他方法中纳入功率考虑的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Power guidelines for process monitoring
Abstract We present a process for designing monitoring procedures that includes practical power guidelines. These guidelines are based upon the average run length (ARL). The specific guideline metric is the ratio of the in-control ARL (ARLic) to the out-of-control ARL (ARLoc). Our recommended design process uses that ARL Ratio, in combination with the ARLic, ARLoc, and ARL curve, to design effective process monitoring procedures. For adequate power, we generally recommend an ARL Ratio of 20 or more and argue that monitoring procedures with ARL Ratios less than 10 should usually be avoided. An area of caution lies between ARL Ratios of 10 and 20, allowing us to propose a stoplight type model for use in monitoring procedure design. We also discuss exceptions to these guidelines as well as a methodology to incorporate power considerations in other approaches to control chart design.
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来源期刊
Quality Engineering
Quality Engineering ENGINEERING, INDUSTRIAL-STATISTICS & PROBABILITY
CiteScore
3.90
自引率
10.00%
发文量
52
审稿时长
>12 weeks
期刊介绍: Quality Engineering aims to promote a rich exchange among the quality engineering community by publishing papers that describe new engineering methods ready for immediate industrial application or examples of techniques uniquely employed. You are invited to submit manuscripts and application experiences that explore: Experimental engineering design and analysis Measurement system analysis in engineering Engineering process modelling Product and process optimization in engineering Quality control and process monitoring in engineering Engineering regression Reliability in engineering Response surface methodology in engineering Robust engineering parameter design Six Sigma method enhancement in engineering Statistical engineering Engineering test and evaluation techniques.
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