A Markov decision process framework for optimal operation of monitored multi-state systems. (December 2018)

• Record Type: Journal Article
• Authors: Compare, Michele; Marelli, Paolo; Baraldi, Piero; Zio, Enrico
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 232:Number 6(2018:Dec.)
• Page Start: 677
• Page End: 689
• Publication Date: 2018-12
• Subjects: Multi-component system -- Markov decision process -- optimal maintenance policy -- optimal operation policy -- prognostics and health management -- condition-based maintenance; Reliability (Engineering) -- Mathematical models -- Periodiclals; Risk assessment -- Mathematical models -- Periodicals; Engineering design -- Mathematical models -- Periodicals; 620.00452
• DOI: 10.1177/1748006X18757077
• Languages: English
• ISSNs: 1748-006X

Abstract

We develop a decision support framework based on Markov decision processes to maximize the profit from the operation of a multi-state system. This framework enables a comprehensive management of the multi-state system, which considers the maintenance decisions together with those on the multi-state system operation setting, that is, its loading condition and configuration. The decisions are informed by a condition monitoring system, which estimates the health state of the multi-state system components. The approach is shown with reference to a mechanical system made up of components affected by fatigue.