Modified short-run statistical process control for test and measurement process

The key characteristics of test and measurement (T&M) manufacturing are short-run, multi-product families and testing at multi-stations. These characteristics render statistical process control (SPC) inefficacious because inherently meagre data do not warrant meaningful control limits. Measureme...

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Main Authors: Koh, C.K., Chin, J.F., Kamaruddin, S.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.22139 /
Published: 2019
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054607120&doi=10.1007%2fs00170-018-2776-1&partnerID=40&md5=295bffc954d2e830a677f795d757f7d5
http://eprints.utp.edu.my/22139/
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spelling utp-eprints.221392019-02-28T07:57:44Z Modified short-run statistical process control for test and measurement process Koh, C.K. Chin, J.F. Kamaruddin, S. The key characteristics of test and measurement (T&M) manufacturing are short-run, multi-product families and testing at multi-stations. These characteristics render statistical process control (SPC) inefficacious because inherently meagre data do not warrant meaningful control limits. Measurement errors increase the risks of false acceptance and rejection, thereby leading to such consequences as unnecessary process adjustments and loss of confidence in SPC. This study presents a modified SPC model that incorporates measurement uncertainty from guard bands into the Z ¯ and W charts, thereby addressing the implications of short runs, multi-stations and measurement errors on SPC. The implementation of this model involves two phases. Phase I retrospective analysis computes the input parameters, such as the standard deviation of the measurement uncertainty, measurement target and estimate of the population standard deviation. Thereafter, five-band setting and sensitivity factor are proposed to estimate process standard deviation to maximise the opportunity to detect the assignable causes with low false-reject rate. Lastly, the Z ¯ and W charts are generated in Phase II using standardised observation technique that considers the measurement target and estimated process standard deviations. Run tests based on Nelson rules interpret the charts. Validation was performed in three case studies in an actual industry. © 2018, Springer-Verlag London Ltd., part of Springer Nature. 2019 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054607120&doi=10.1007%2fs00170-018-2776-1&partnerID=40&md5=295bffc954d2e830a677f795d757f7d5 Koh, C.K. and Chin, J.F. and Kamaruddin, S. (2019) Modified short-run statistical process control for test and measurement process. International Journal of Advanced Manufacturing Technology, 100 (5-8). pp. 1531-1548. http://eprints.utp.edu.my/22139/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description The key characteristics of test and measurement (T&M) manufacturing are short-run, multi-product families and testing at multi-stations. These characteristics render statistical process control (SPC) inefficacious because inherently meagre data do not warrant meaningful control limits. Measurement errors increase the risks of false acceptance and rejection, thereby leading to such consequences as unnecessary process adjustments and loss of confidence in SPC. This study presents a modified SPC model that incorporates measurement uncertainty from guard bands into the Z ¯ and W charts, thereby addressing the implications of short runs, multi-stations and measurement errors on SPC. The implementation of this model involves two phases. Phase I retrospective analysis computes the input parameters, such as the standard deviation of the measurement uncertainty, measurement target and estimate of the population standard deviation. Thereafter, five-band setting and sensitivity factor are proposed to estimate process standard deviation to maximise the opportunity to detect the assignable causes with low false-reject rate. Lastly, the Z ¯ and W charts are generated in Phase II using standardised observation technique that considers the measurement target and estimated process standard deviations. Run tests based on Nelson rules interpret the charts. Validation was performed in three case studies in an actual industry. © 2018, Springer-Verlag London Ltd., part of Springer Nature.
format Article
author Koh, C.K.
Chin, J.F.
Kamaruddin, S.
spellingShingle Koh, C.K.
Chin, J.F.
Kamaruddin, S.
Modified short-run statistical process control for test and measurement process
author_sort Koh, C.K.
title Modified short-run statistical process control for test and measurement process
title_short Modified short-run statistical process control for test and measurement process
title_full Modified short-run statistical process control for test and measurement process
title_fullStr Modified short-run statistical process control for test and measurement process
title_full_unstemmed Modified short-run statistical process control for test and measurement process
title_sort modified short-run statistical process control for test and measurement process
publishDate 2019
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054607120&doi=10.1007%2fs00170-018-2776-1&partnerID=40&md5=295bffc954d2e830a677f795d757f7d5
http://eprints.utp.edu.my/22139/
_version_ 1741196574408572928
score 11.62408

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