CUSUM Schemes for Monitoring Prespecified Changes in Linear Profiles. (7th July 2016)
- Record Type:
- Journal Article
- Title:
- CUSUM Schemes for Monitoring Prespecified Changes in Linear Profiles. (7th July 2016)
- Main Title:
- CUSUM Schemes for Monitoring Prespecified Changes in Linear Profiles
- Authors:
- Zhang, Yang
Shang, Yanfen
He, Zhen
Wang, Qing - Abstract:
- Abstract : Because of the characteristics of a system or process, several prespecified changes may happen in some statistical process control applications. Thus, one possible and challenging problem in profile monitoring is detecting changes away from the 'normal' profile toward one of several prespecified 'bad' profiles. In this article, to monitor the prespecified changes in linear profiles, two two‐sided cumulative sum (CUSUM) schemes are proposed based on Student's t ‐statistic, which use two separate statistics and a single statistic, respectively. Simulation results show that the CUSUM scheme with a single statistic uniformly outperforms that with two separate statistics. Besides, both CUSUM schemes perform better than alternative methods in detecting small shifts in prespecified changes, and become comparable on detecting moderate or large shifts when the number of observations in each profile is large. To overcome the weakness in the proposed CUSUM methods, two modified CUSUM schemes are developed using z ‐statistic and studied when the in‐control parameters are estimated. Simulation results indicate that the modified CUSUM chart with a single charting statistic slightly outperforms that with two separate statistics in terms of the average run length and its standard deviation. Finally, illustrative examples indicate that the CUSUM schemes are effective. Copyright © 2016 John Wiley & Sons, Ltd.
- Is Part Of:
- Quality and reliability engineering international. Volume 33:Number 3(2017:Apr.)
- Journal:
- Quality and reliability engineering international
- Issue:
- Volume 33:Number 3(2017:Apr.)
- Issue Display:
- Volume 33, Issue 3 (2017)
- Year:
- 2017
- Volume:
- 33
- Issue:
- 3
- Issue Sort Value:
- 2017-0033-0003-0000
- Page Start:
- 579
- Page End:
- 594
- Publication Date:
- 2016-07-07
- Subjects:
- average run length (ARL) -- profile monitoring -- statistical process control (SPC) -- standard deviation of the average run length (SDARL) -- Student's t‐statistic
Reliability (Engineering) -- Periodicals
Quality control -- Periodicals
High technology -- Periodicals
620.00452 - Journal URLs:
- http://www3.interscience.wiley.com/cgi-bin/jhome/3680 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/qre.2042 ↗
- Languages:
- English
- ISSNs:
- 0748-8017
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7168.137300
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 286.xml