Response surfaces, blocking, and split plots: A predictive distribution case study

IF 1.3 4区 工程技术 Q4 ENGINEERING, INDUSTRIAL
John J. Peterson
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引用次数: 0

Abstract

Abstract This article presents a case study re-analysis of a complex response-factor data set involving a split-plot design with blocking for two quality responses. The analysis presented herein makes use of multivariate predictive distributions to both optimize and quantify the risk of meeting specifications. This article shows how a modern approach using predictive distributions can provide deeper insight and improved process optimization over the use of classical response surface methodology tools such as “overlapping means” plots and (mean-based) desirability functions. It is shown how the R and the Stan programming languages are used to facilitate the analysis.
响应面,阻塞和分裂图:预测分布案例研究
摘要:本文介绍了一个案例研究,对一个复杂的响应因子数据集进行了重新分析,该数据集涉及两个质量响应的分割图设计。本文的分析利用多元预测分布来优化和量化满足规范的风险。本文展示了使用预测分布的现代方法如何比使用经典响应面方法工具(如“重叠平均值”图和(基于平均值的)可取性函数)提供更深入的见解和改进的流程优化。它展示了如何使用R和Stan编程语言来促进分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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