Dynamic Maintenance, Production and Inspection Policies, for a Single-Stage, Multi-State Production System

Mohammad M. Aldurgam*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Over the past 20 years, integrated decision making for production systems has gained the interest of researchers and practitioners. Many studies have shown that integrated decision making can lead to substantial amount of savings. Yet, a few research work has been conducted on the areas of integrated maintenance, production and quality in dynamic environments. This paper provides an integrated multi-period, maintenance, production and quality-inspection scheduling model, which is formulated as a Markov decision process. The model minimizes the total expected maintenance, production and quality inspection costs. The structural properties of the proposed model are mathematically investigated and with using sensitivity analysis, practical insights are also provided. We mathematically provide conditions to guarantee that the optimal inspection policy is monotone non-decreasing in the state of the machine. Furthermore, we show that the optimal production policy decreases by one unit as the state of inventory increases by one unit. Sensitivity analysis demonstrates that the production parameters affect both, maintenance and inspection decisions. In addition, the maintenance parameters affect inspection decisions. Finally, it is found that among the inspection parameters (i.e., cost-of-inspection and inspection-errors), type-II error mainly affects maintenance decisions.

Original languageEnglish
Article number9108208
Pages (from-to)105645-105658
Number of pages14
JournalIEEE Access
StatePublished - 2020

Bibliographical note

Funding Information:
This work was supported by the Deanship of Scientific Research, King Fahd University of Petroleum and Minerals (KFUPM), under Grant SB181023.

Publisher Copyright:
© 2013 IEEE.


  • Decision making under uncertainty
  • Markov decision process
  • inspection errors
  • integrated production
  • maintenance and quality

ASJC Scopus subject areas

  • Computer Science (all)
  • Materials Science (all)
  • Engineering (all)


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