SPC charting procedure for monitoring of small and large shifts in process mean

The research obj ectives are to study the effectiveness of traditional control charts that are Shewharf, Two-Sided CUS1ll11 and EWlvfA in monitoring small and large process mean shifts and to propose an improved statistical process control charting procedures that effective for monitoring all...

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Main Author: Masood, Ibrahim
Format: Thesis
Language:English
Published: 2004
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Online Access:http://eprints.uthm.edu.my/7652/1/24p%20IBRAHIM%20MASOOD.pdf
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spelling my.uthm.eprints.76522022-09-08T02:18:14Z http://eprints.uthm.edu.my/7652/ SPC charting procedure for monitoring of small and large shifts in process mean Masood, Ibrahim TS155-194 Production management. Operations management The research obj ectives are to study the effectiveness of traditional control charts that are Shewharf, Two-Sided CUS1ll11 and EWlvfA in monitoring small and large process mean shifts and to propose an improved statistical process control charting procedures that effective for monitoring all process mean shifts. Process mean shift can be described as unstable patterns such as shift pattern itself and trend pattern. Average run length (ARL), Type I Error and Type II Error are used as the performance measures. The charting procedures were coded in MATLAB program and ex1:ensive simulation experiments were conducted. Design of Experiment (DOE) methods were applied in selecting the suitable design parameters of control charts before conducting the detail ARL simulations. The ARL simulation identifies each control chart monitoring advantages and disadvantages. In general, Two-Sided CUS1l111 and EWlvfA were confirmed effective for detecting small process shifts, while Shell'harf only effective for large process shifts. Specifically, Two-Sided Cusum with (k, h) = (0.5,4.77) and (0.75, 3.34) were identified produced small Type I error, so effective for monitoring small process mean shift, more effective than ETYMA and close to Nelson's Run Rules performance for 0.75cr to 2.5cr shift range. The findings were validated using a few real process data. The concurrent application of Shewharf, Two-Sided CUS1ll11 with (k, h) = (0.5,4.77) and (0.75, 3.34) were proposed as an improved charting scheme. It is observed more effective than the Combined Shewharf-CUS1ll11 which was recommended by Lucas (1982). However, Nelson's Run Rules is not recommended because it provides large Type I error even so effective for monitoring process shift. The findings were confirmed and detailed the individual Nelson Run Rules performances stated by Nelson (1985), except rules for detecting stratification. Finding on different rules gave different 'rate of false signal' (RFS), contradicted with result based on Monte Carlo method (Nelson, 1985) but confirmed the result from Trietsch (1997). Findings on EWMA were confirmed Montgomery (1996) which stated that small constant (A) more sensitive for identifying small shifts while large A better for identifying large shifts. 2004-11 Thesis NonPeerReviewed text en http://eprints.uthm.edu.my/7652/1/24p%20IBRAHIM%20MASOOD.pdf Masood, Ibrahim (2004) SPC charting procedure for monitoring of small and large shifts in process mean. Masters thesis, Universiti Teknologi Malaysia.
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic TS155-194 Production management. Operations management
spellingShingle TS155-194 Production management. Operations management
Masood, Ibrahim
SPC charting procedure for monitoring of small and large shifts in process mean
description The research obj ectives are to study the effectiveness of traditional control charts that are Shewharf, Two-Sided CUS1ll11 and EWlvfA in monitoring small and large process mean shifts and to propose an improved statistical process control charting procedures that effective for monitoring all process mean shifts. Process mean shift can be described as unstable patterns such as shift pattern itself and trend pattern. Average run length (ARL), Type I Error and Type II Error are used as the performance measures. The charting procedures were coded in MATLAB program and ex1:ensive simulation experiments were conducted. Design of Experiment (DOE) methods were applied in selecting the suitable design parameters of control charts before conducting the detail ARL simulations. The ARL simulation identifies each control chart monitoring advantages and disadvantages. In general, Two-Sided CUS1l111 and EWlvfA were confirmed effective for detecting small process shifts, while Shell'harf only effective for large process shifts. Specifically, Two-Sided Cusum with (k, h) = (0.5,4.77) and (0.75, 3.34) were identified produced small Type I error, so effective for monitoring small process mean shift, more effective than ETYMA and close to Nelson's Run Rules performance for 0.75cr to 2.5cr shift range. The findings were validated using a few real process data. The concurrent application of Shewharf, Two-Sided CUS1ll11 with (k, h) = (0.5,4.77) and (0.75, 3.34) were proposed as an improved charting scheme. It is observed more effective than the Combined Shewharf-CUS1ll11 which was recommended by Lucas (1982). However, Nelson's Run Rules is not recommended because it provides large Type I error even so effective for monitoring process shift. The findings were confirmed and detailed the individual Nelson Run Rules performances stated by Nelson (1985), except rules for detecting stratification. Finding on different rules gave different 'rate of false signal' (RFS), contradicted with result based on Monte Carlo method (Nelson, 1985) but confirmed the result from Trietsch (1997). Findings on EWMA were confirmed Montgomery (1996) which stated that small constant (A) more sensitive for identifying small shifts while large A better for identifying large shifts.
format Thesis
author Masood, Ibrahim
author_facet Masood, Ibrahim
author_sort Masood, Ibrahim
title SPC charting procedure for monitoring of small and large shifts in process mean
title_short SPC charting procedure for monitoring of small and large shifts in process mean
title_full SPC charting procedure for monitoring of small and large shifts in process mean
title_fullStr SPC charting procedure for monitoring of small and large shifts in process mean
title_full_unstemmed SPC charting procedure for monitoring of small and large shifts in process mean
title_sort spc charting procedure for monitoring of small and large shifts in process mean
publishDate 2004
url http://eprints.uthm.edu.my/7652/1/24p%20IBRAHIM%20MASOOD.pdf
http://eprints.uthm.edu.my/7652/
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score 13.209306