An adaptive EWMA scheme-based CUSUM accumulation error for efficient monitoring of process location

The examination of product characteristics using a statistical tool is an important step in a manufacturing environment to ensure product quality. Several methods are employed for maintaining product quality assurance. Quality control charts, which utilize statistical methods, are normally used to d...

Full description

Saved in:
Bibliographic Details
Main Authors: Zaman, B., Lee, M. H., Riaz, M., Abujiya, M. R.
Format: Article
Published: John Wiley and Sons Ltd 2017
Subjects:
Online Access:http://eprints.utm.my/id/eprint/75715/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85035083482&doi=10.1002%2fqre.2203&partnerID=40&md5=115e0fbb65021eb27234c34669f04ca1
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.75715
record_format eprints
spelling my.utm.757152018-04-27T01:47:36Z http://eprints.utm.my/id/eprint/75715/ An adaptive EWMA scheme-based CUSUM accumulation error for efficient monitoring of process location Zaman, B. Lee, M. H. Riaz, M. Abujiya, M. R. QA Mathematics The examination of product characteristics using a statistical tool is an important step in a manufacturing environment to ensure product quality. Several methods are employed for maintaining product quality assurance. Quality control charts, which utilize statistical methods, are normally used to detect special causes. Shewhart control charts are popular; their only limitation is that they are effective in handling only large shifts. For handling small shifts, the cumulative sum (CUSUM) and the exponential weighted moving average (EWMA) are more practical. For handling both small and large shifts, adaptive control charts are used. In this study, we proposed a new adaptive EWMA scheme. This scheme is based on CUSUM accumulation error for detection of wide range of shifts in the process location. The CUSUM features in the proposed scheme help with identification of prior shifts. The proposed scheme uses Huber and Tukey bisquare functions for an efficient shift detection. We have used average run length (ARL) as performance indicator for comparison, and our proposed scheme outperformed some of the existing schemes. An example that uses real-life data is also provided to demonstrate the implementation of the proposed scheme. John Wiley and Sons Ltd 2017 Article PeerReviewed Zaman, B. and Lee, M. H. and Riaz, M. and Abujiya, M. R. (2017) An adaptive EWMA scheme-based CUSUM accumulation error for efficient monitoring of process location. Quality and Reliability Engineering International, 33 (8). pp. 2463-2482. ISSN 0748-8017 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85035083482&doi=10.1002%2fqre.2203&partnerID=40&md5=115e0fbb65021eb27234c34669f04ca1
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA Mathematics
spellingShingle QA Mathematics
Zaman, B.
Lee, M. H.
Riaz, M.
Abujiya, M. R.
An adaptive EWMA scheme-based CUSUM accumulation error for efficient monitoring of process location
description The examination of product characteristics using a statistical tool is an important step in a manufacturing environment to ensure product quality. Several methods are employed for maintaining product quality assurance. Quality control charts, which utilize statistical methods, are normally used to detect special causes. Shewhart control charts are popular; their only limitation is that they are effective in handling only large shifts. For handling small shifts, the cumulative sum (CUSUM) and the exponential weighted moving average (EWMA) are more practical. For handling both small and large shifts, adaptive control charts are used. In this study, we proposed a new adaptive EWMA scheme. This scheme is based on CUSUM accumulation error for detection of wide range of shifts in the process location. The CUSUM features in the proposed scheme help with identification of prior shifts. The proposed scheme uses Huber and Tukey bisquare functions for an efficient shift detection. We have used average run length (ARL) as performance indicator for comparison, and our proposed scheme outperformed some of the existing schemes. An example that uses real-life data is also provided to demonstrate the implementation of the proposed scheme.
format Article
author Zaman, B.
Lee, M. H.
Riaz, M.
Abujiya, M. R.
author_facet Zaman, B.
Lee, M. H.
Riaz, M.
Abujiya, M. R.
author_sort Zaman, B.
title An adaptive EWMA scheme-based CUSUM accumulation error for efficient monitoring of process location
title_short An adaptive EWMA scheme-based CUSUM accumulation error for efficient monitoring of process location
title_full An adaptive EWMA scheme-based CUSUM accumulation error for efficient monitoring of process location
title_fullStr An adaptive EWMA scheme-based CUSUM accumulation error for efficient monitoring of process location
title_full_unstemmed An adaptive EWMA scheme-based CUSUM accumulation error for efficient monitoring of process location
title_sort adaptive ewma scheme-based cusum accumulation error for efficient monitoring of process location
publisher John Wiley and Sons Ltd
publishDate 2017
url http://eprints.utm.my/id/eprint/75715/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85035083482&doi=10.1002%2fqre.2203&partnerID=40&md5=115e0fbb65021eb27234c34669f04ca1
_version_ 1643657140712243200
score 13.211869