EconPapers    
Economics at your fingertips  
 

Delayed maintenance policy optimisation based on control chart

Guojun Zhang, Yuhao Deng, Haiping Zhu and Hui Yin

International Journal of Production Research, 2015, vol. 53, issue 2, 341-353

Abstract: Data sharing between statistic process control (SPC) and condition-based maintenance is valuable and the joint optimisation has been studied, mostly focusing on the SPC control chart limits. Traditionally, maintenance is taken as a response to the control chart alarms, as soon as the alarm is released. This may not be a good decision due to the existence of false alarms and the loss of production interruptions. So this paper proposed a delayed maintenance policy. This policy allows a delay time for the detection and maintenance after an alarm. The operational state probabilities during the delayed period are estimated by Bayesian theory, and a Markov model is built for the monitoring–maintenance process. The model is validated by a Tecnomatix-based simulation, and then used to optimise the average delay time as well as the sampling parameters. Numerical results show that the improvements do exist in some cases, but it depends on the production conditions. Suggestions about when to perform delayed maintenance are also given through factorial analysis.

Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2014.923948 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:53:y:2015:i:2:p:341-353

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2014.923948

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:tprsxx:v:53:y:2015:i:2:p:341-353