Quantitative techniques to evaluate process stability

Brenda S. Ramirez; George Runger

doi:10.1080/08982110500403581

Quantitative techniques to evaluate process stability

Brenda S. Ramirez, George Runger

Research output: Contribution to journal › Article › peer-review

22 Scopus citations

Abstract

There have been numerous measures proposed to quantify the capability of a process using statistics such as C_p, C _pk, and C_pm. There are even tests of hypothesis to see if the calculated C_p or C_pk exceeds some constant. However, there are few quantitative summaries to use as a starting point to assess the overall in-control performance of a process. In this article, we propose three measures that can be used to assess the stability of a process and classify the process parameter as stable or unstable. Test criteria for each of the three measures are suggested, and their overall performance under certain conditions are studied. These concepts are demonstrated using three case studies that are detailed throughout the article.

Original language	English (US)
Pages (from-to)	53-68
Number of pages	16
Journal	Quality Engineering
Volume	18
Issue number	1
DOIs	https://doi.org/10.1080/08982110500403581
State	Published - Jun 2006

Keywords

ANOVA
Stability ratio
Statistical process control
Western Electric rules

ASJC Scopus subject areas

Safety, Risk, Reliability and Quality
Industrial and Manufacturing Engineering

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10.1080/08982110500403581

Cite this

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title = "Quantitative techniques to evaluate process stability",

abstract = "There have been numerous measures proposed to quantify the capability of a process using statistics such as Cp, C pk, and Cpm. There are even tests of hypothesis to see if the calculated Cp or Cpk exceeds some constant. However, there are few quantitative summaries to use as a starting point to assess the overall in-control performance of a process. In this article, we propose three measures that can be used to assess the stability of a process and classify the process parameter as stable or unstable. Test criteria for each of the three measures are suggested, and their overall performance under certain conditions are studied. These concepts are demonstrated using three case studies that are detailed throughout the article.",

keywords = "ANOVA, Stability ratio, Statistical process control, Western Electric rules",

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note = "Funding Information: George C. Runger, Ph.D., is a Professor in the department of Industrial Engineering at Arizona State University. His research is on real-time monitoring and control, data mining, and other data analysis methods with a focus on large, complex, multivariate data streams. He has more than 100 research publications in these areas. His work is funded by grants from the National Science Foundation and corporations. In addition to academic work, he was a senior engineer at IBM. He holds degrees in industrial engineering and statistics.",

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N2 - There have been numerous measures proposed to quantify the capability of a process using statistics such as Cp, C pk, and Cpm. There are even tests of hypothesis to see if the calculated Cp or Cpk exceeds some constant. However, there are few quantitative summaries to use as a starting point to assess the overall in-control performance of a process. In this article, we propose three measures that can be used to assess the stability of a process and classify the process parameter as stable or unstable. Test criteria for each of the three measures are suggested, and their overall performance under certain conditions are studied. These concepts are demonstrated using three case studies that are detailed throughout the article.

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KW - Stability ratio

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KW - Western Electric rules

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Quantitative techniques to evaluate process stability

Abstract

Keywords

ASJC Scopus subject areas

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