Process yield analysis for multivariate linear profiles

Fu Kwun Wang

doi:10.1080/16843703.2016.1169676

Process yield analysis for multivariate linear profiles

Fu Kwun Wang^*

^*Corresponding author for this work

National Taiwan University of Science and Technology

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

13 Scopus citations

Abstract

Abstract: Process capability analysis plays an important role in statistical quality control. We present the process yield index TS_pkA to evaluate the process yield for multivariate linear profiles in manufacturing processes. This index provides an exact measure of the process yield. In addition, an approximate confidence interval for TS_pkA is constructed. A simulation study is conducted to assess the performance of the proposed method for multivariate linear profiles data under mutually independent normality and multivariate normality. The simulation results confirm that the estimated TS_pkA is close to the target value with smaller standard deviation as the sample size increases.

Original language	English
Pages (from-to)	124-138
Number of pages	15
Journal	Quality Technology and Quantitative Management
Volume	13
Issue number	2
DOIs	https://doi.org/10.1080/16843703.2016.1169676
State	Published - 02 04 2016
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2016 International Chinese Association of Quantitative Management.

Keywords

Confidence interval
multivariate linear profiles
process capability analysis
process yield

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1080/16843703.2016.1169676

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title = "Process yield analysis for multivariate linear profiles",

abstract = "Abstract: Process capability analysis plays an important role in statistical quality control. We present the process yield index TSpkA to evaluate the process yield for multivariate linear profiles in manufacturing processes. This index provides an exact measure of the process yield. In addition, an approximate confidence interval for TSpkA is constructed. A simulation study is conducted to assess the performance of the proposed method for multivariate linear profiles data under mutually independent normality and multivariate normality. The simulation results confirm that the estimated TSpkA is close to the target value with smaller standard deviation as the sample size increases.",

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N2 - Abstract: Process capability analysis plays an important role in statistical quality control. We present the process yield index TSpkA to evaluate the process yield for multivariate linear profiles in manufacturing processes. This index provides an exact measure of the process yield. In addition, an approximate confidence interval for TSpkA is constructed. A simulation study is conducted to assess the performance of the proposed method for multivariate linear profiles data under mutually independent normality and multivariate normality. The simulation results confirm that the estimated TSpkA is close to the target value with smaller standard deviation as the sample size increases.

AB - Abstract: Process capability analysis plays an important role in statistical quality control. We present the process yield index TSpkA to evaluate the process yield for multivariate linear profiles in manufacturing processes. This index provides an exact measure of the process yield. In addition, an approximate confidence interval for TSpkA is constructed. A simulation study is conducted to assess the performance of the proposed method for multivariate linear profiles data under mutually independent normality and multivariate normality. The simulation results confirm that the estimated TSpkA is close to the target value with smaller standard deviation as the sample size increases.

KW - Confidence interval

KW - multivariate linear profiles

KW - process capability analysis

KW - process yield

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JO - Quality Technology and Quantitative Management

JF - Quality Technology and Quantitative Management

IS - 2

ER -

Process yield analysis for multivariate linear profiles

Abstract

Bibliographical note

Keywords

UN SDGs

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