Modified Statistical Process Control For Short Runs Test And Measurement Process To Reduce False Alarm

The key characteristics of test and measurement (T&M) manufacturing are short production runs, multi-product families and testing at multi-stations. Classical Shewhart control charts, namely x̄ chart and R chart have been widely used in statistical process control (SPC). Short production runs in...

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Main Author:	Koh, Chin Kok
Format:	Thesis
Language:	English
Published:	2018
Subjects:	T Technology TJ1-1570 Mechanical engineering and machinery
Online Access:	http://eprints.usm.my/47816/1/Modified%20Statistical%20Process%20Control%20For%20Short%20Runs%20Test%20And%20Measurement%20Process%20To%20Reduce%20False%20Alarm.pdf
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id	my-usm-ep.47816
record_format	uketd_dc
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	T Technology TJ1-1570 Mechanical engineering and machinery
spellingShingle	T Technology TJ1-1570 Mechanical engineering and machinery Koh, Chin Kok Modified Statistical Process Control For Short Runs Test And Measurement Process To Reduce False Alarm
description	The key characteristics of test and measurement (T&M) manufacturing are short production runs, multi-product families and testing at multi-stations. Classical Shewhart control charts, namely x̄ chart and R chart have been widely used in statistical process control (SPC). Short production runs in T&M render these charts inefficacious as inherent meager data do not warrant meaningful control limits. Measurement errors increase the risks of false acceptance and rejection, thereby leading to consequences such as unnecessary process adjustment and loss of confidence in SPC. Industry practice allows the installation of Guard band, e.g., through Guide to the Expression of Uncertainty in Measurement (GUM) to reduce the width of acceptance limit, as an indirect way to compensate the measurement errors. Past related works which presented standardized observations technique is highly recommended due to its simplicity and practicality. However, the concern is that this technique requires sufficient data to calculate the control limits and it does not deal with the effect of measurement errors. Based on this premise, the research objective is to develop a modified SPC model by considering measurement uncertainty in modified control charts (Z chart and W chart) for short runs T&M process in multi-stations. 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 S–factor are proposed to estimate process standard deviation to maximize the the opportunity to detect assignable causes with low false-reject rate. Lastly, the modified Z chart and W chart are generated in Phase II using standardized observations technique that considers the measurement target and the estimated process standard deviations. Run tests based on Nelson’s rules to interpret the control charts. In terms of validation, three case studies, labeled as Case I, Case II and Case III were conducted with different ratios of standard deviations in measurement uncertainty and population to demonstrate the effectiveness of the proposed model. A complete year’s data samples were collected from products tested at multi-stations in a T&M manufacturing facility at Bayan Lepas, Penang. For Case I with the measurement error is negligible and does not affect the process standard deviation; the results indicate that there were no false alarm points found in all methods. In Case II with the measurement error may noticeably affect the process standard deviation, and the results show that the model with Five-band setting and S-factor reduced the false alarm rate by 100% in comparison to the classical Shewhart method, except for the Five-band setting which has a smaller sustained shift (25% false alarm) was falsely detected in station WH05. In Case III with the measurement error is relatively larger and appeared to be more significantly affecting the process standard deviation; the results reveal that both proposed methods performed well in modified Z and W charts, which reduced false alarm rate by 50% for station WH05, 0% for station WH06 and 37.5% for station WH07. As a conclusion, the research has proposed and demonstrated the modified SPC model can address the understudied issues caused by short production runs and measurement errors. The model is practical for T&M manufacturing to reduce false alarms and to prevent unnecessary process adjustment.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Koh, Chin Kok
author_facet	Koh, Chin Kok
author_sort	Koh, Chin Kok
title	Modified Statistical Process Control For Short Runs Test And Measurement Process To Reduce False Alarm
title_short	Modified Statistical Process Control For Short Runs Test And Measurement Process To Reduce False Alarm
title_full	Modified Statistical Process Control For Short Runs Test And Measurement Process To Reduce False Alarm
title_fullStr	Modified Statistical Process Control For Short Runs Test And Measurement Process To Reduce False Alarm
title_full_unstemmed	Modified Statistical Process Control For Short Runs Test And Measurement Process To Reduce False Alarm
title_sort	modified statistical process control for short runs test and measurement process to reduce false alarm
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Kejuruteraan Mekanik
publishDate	2018
url	http://eprints.usm.my/47816/1/Modified%20Statistical%20Process%20Control%20For%20Short%20Runs%20Test%20And%20Measurement%20Process%20To%20Reduce%20False%20Alarm.pdf
_version_	1747821834361896960
spelling	my-usm-ep.478162021-11-17T03:42:13Z Modified Statistical Process Control For Short Runs Test And Measurement Process To Reduce False Alarm 2018-09-01 Koh, Chin Kok T Technology TJ1-1570 Mechanical engineering and machinery The key characteristics of test and measurement (T&M) manufacturing are short production runs, multi-product families and testing at multi-stations. Classical Shewhart control charts, namely x̄ chart and R chart have been widely used in statistical process control (SPC). Short production runs in T&M render these charts inefficacious as inherent meager data do not warrant meaningful control limits. Measurement errors increase the risks of false acceptance and rejection, thereby leading to consequences such as unnecessary process adjustment and loss of confidence in SPC. Industry practice allows the installation of Guard band, e.g., through Guide to the Expression of Uncertainty in Measurement (GUM) to reduce the width of acceptance limit, as an indirect way to compensate the measurement errors. Past related works which presented standardized observations technique is highly recommended due to its simplicity and practicality. However, the concern is that this technique requires sufficient data to calculate the control limits and it does not deal with the effect of measurement errors. Based on this premise, the research objective is to develop a modified SPC model by considering measurement uncertainty in modified control charts (Z chart and W chart) for short runs T&M process in multi-stations. 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 S–factor are proposed to estimate process standard deviation to maximize the the opportunity to detect assignable causes with low false-reject rate. Lastly, the modified Z chart and W chart are generated in Phase II using standardized observations technique that considers the measurement target and the estimated process standard deviations. Run tests based on Nelson’s rules to interpret the control charts. In terms of validation, three case studies, labeled as Case I, Case II and Case III were conducted with different ratios of standard deviations in measurement uncertainty and population to demonstrate the effectiveness of the proposed model. A complete year’s data samples were collected from products tested at multi-stations in a T&M manufacturing facility at Bayan Lepas, Penang. For Case I with the measurement error is negligible and does not affect the process standard deviation; the results indicate that there were no false alarm points found in all methods. In Case II with the measurement error may noticeably affect the process standard deviation, and the results show that the model with Five-band setting and S-factor reduced the false alarm rate by 100% in comparison to the classical Shewhart method, except for the Five-band setting which has a smaller sustained shift (25% false alarm) was falsely detected in station WH05. In Case III with the measurement error is relatively larger and appeared to be more significantly affecting the process standard deviation; the results reveal that both proposed methods performed well in modified Z and W charts, which reduced false alarm rate by 50% for station WH05, 0% for station WH06 and 37.5% for station WH07. As a conclusion, the research has proposed and demonstrated the modified SPC model can address the understudied issues caused by short production runs and measurement errors. The model is practical for T&M manufacturing to reduce false alarms and to prevent unnecessary process adjustment. 2018-09 Thesis http://eprints.usm.my/47816/ http://eprints.usm.my/47816/1/Modified%20Statistical%20Process%20Control%20For%20Short%20Runs%20Test%20And%20Measurement%20Process%20To%20Reduce%20False%20Alarm.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Kejuruteraan Mekanik

Modified Statistical Process Control For Short Runs Test And Measurement Process To Reduce False Alarm

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