95
Views
10
CrossRef citations to date
0
Altmetric
Articles

Joint optimisation of double warning T2-Hotelling chart and maintenance policy with multiple assignable causes

, &
Pages 465-488 | Received 12 Jun 2019, Accepted 30 Oct 2019, Published online: 02 Dec 2019
 

ABSTRACT

Statistical process monitoring (SPM) and maintenance management as two key tools for process management can create profound economic benefits, particularly when they are coordinated. This paper demonstrates the value of integrating SPM and maintenance by presenting a multi-objective model consisting of both economic and statistical criteria. Furthermore, to more adapt to complex manufacturing systems, the proposed model consists of two features: (1) monitoring several correlated quality characteristics by designing a double warning lines ‘T2-Hotelling’ chart; and (2) considering the probability of occurrence for more than one assignable cause (AC). To show the effectiveness of the proposed integrated model, two comparative studies are conducted. The first one confirms that the integration of SPM and maintenance policy leads to more effective performance in both economic and statistical viewpoints. The latter results demonstrate that the proposed model outperforms the corresponding single objective models.

Disclosure statement

No potential conflict of interest was reported by the authors.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,209.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.