On evaluating the measurement capability of high-quality processes

J. J. Lyu; M. N. Chen

doi:10.1109/IEEM.2008.4738231

On evaluating the measurement capability of high-quality processes

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Measurement systems analysis (MSA) ensures that the required data can reliably perform quality improvement initiatives. The common program to assess the precision of a measurement system is the gauge repeatability and reproducibility(R&R) study. Few investigations relate to the gauge R&R study for attribute data despite a need for industrial applications. Industries with near zero-defect manufacturing environments often experience occasional nonconformities in some samples when random shocks arise. The standard MSA may fail to identify defective data from high-quality processes. This study proposes an attribute gauge system to enhance the capability of the measurement system. The process and potential of the proposed system is illustrated using a manufacturing case.

Original language	English
Title of host publication	2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008
Pages	2046-2050
Number of pages	5
DOIs	https://doi.org/10.1109/IEEM.2008.4738231
Publication status	Published - 2008 Dec 1
Event	2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008 - Singapore, Singapore Duration: 2008 Dec 8 → 2008 Dec 11

Publication series

Name	2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008

Other

Other	2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008
Country/Territory	Singapore
City	Singapore
Period	08-12-08 → 08-12-11

All Science Journal Classification (ASJC) codes

Management Information Systems
Industrial and Manufacturing Engineering

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10.1109/IEEM.2008.4738231

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Lyu, J. J., & Chen, M. N. (2008). On evaluating the measurement capability of high-quality processes. In 2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008 (pp. 2046-2050). [4738231] (2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008). https://doi.org/10.1109/IEEM.2008.4738231

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abstract = "Measurement systems analysis (MSA) ensures that the required data can reliably perform quality improvement initiatives. The common program to assess the precision of a measurement system is the gauge repeatability and reproducibility(R&R) study. Few investigations relate to the gauge R&R study for attribute data despite a need for industrial applications. Industries with near zero-defect manufacturing environments often experience occasional nonconformities in some samples when random shocks arise. The standard MSA may fail to identify defective data from high-quality processes. This study proposes an attribute gauge system to enhance the capability of the measurement system. The process and potential of the proposed system is illustrated using a manufacturing case.",

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Lyu, JJ & Chen, MN 2008, On evaluating the measurement capability of high-quality processes. in 2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008., 4738231, 2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008, pp. 2046-2050, 2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008, Singapore, Singapore, 08-12-08. https://doi.org/10.1109/IEEM.2008.4738231

On evaluating the measurement capability of high-quality processes. / Lyu, J. J.; Chen, M. N.

2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008. 2008. p. 2046-2050 4738231 (2008 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2008).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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ER -

On evaluating the measurement capability of high-quality processes

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