A novel performance evaluation model for MRO management indicators of high-end equipment

Ling Li, Min Liu, Weiming Shen and Guoqing Cheng

International Journal of Production Research, 2019, vol. 57, issue 21, 6740-6757

Abstract: High-end equipment oriented maintenance, repair and operation (MRO) management is crucial for asset intensive industries. The existing works mainly focus on providing the best possible joint optimisation for production and maintenance management without aiming at the complicated relationships among them. In the intelligence-connected era, the rapid development of Internet of things and big data technologies enables us to access, collect, and store the industrial big data, which is especially necessary for MRO management indicator evaluation, and so we try to apply big data analysis to visualise the system structure of complicated relationships among MRO indicators at different management levels. In this paper, the decision-making trial and evaluation laboratory (DEMATEL) and improved analytical network process (ANP) are applied to build the performance evaluation model for MRO management indicators, in which DEMATEL is utilised to quantify the system structure of different management levels, and the improved ANP is introduced to calculate relative weights of corresponding indicators. The results point out to managers which indicators should deserve more attention in MRO management decision-making as well as joint optimisation for production and maintenance management. A case study illustrates the feasibility and practicality of the proposed model.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2019.1566654 (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:57:y:2019:i:21:p:6740-6757

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

DOI: 10.1080/00207543.2019.1566654

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 ().