A decision dependent stochastic process model for repairable systems with applications. (December 2015)

• Record Type: Journal Article
• Authors: Zantek, Paul F.; Hanson, Timothy; Damien, Paul; Popova, Elmira
• Is Part Of: Operations research perspectives. Volume 2(2015)
• Page Start: 73
• Page End: 80
• Publication Date: 2015-12
• Subjects: Kijima model -- Decision dependence -- Maintenance schedule -- Repairable system -- Spiral down effect; Operations research -- Periodicals; Management science -- Periodicals; 658.403405
• DOI: 10.1016/j.orp.2015.03.002
• Languages: English
• ISSNs: 2214-7160

Abstract

Abstract: Management decisions regarding maintenance protocols critically hinge on the underlying probability distribution of the time between failures in most repairable systems. Replacement of the system with a new one resets the system age to zero, whereas a repair does not alter the system age but may shift the parameters of the failure-time distribution. Additionally, maintenance decisions lead to left-truncated observations, and right-censored observations. Thus, the underlying stochastic process governing a repairable system evolves based on the management decision taken. This paper mathematically formalizes the notion of how management actions impact the functioning of a repairable system over time by developing a new stochastic process model for such systems. The proposed model is illustrated using both simulated and real data. The proposed model compares favorably to other models for well-known data on Boeing airplanes. The model is further illustrated and compared to other models on failure time and maintenance data stemming from the South Texas Project nuclear power plant.