Optimum maintenance strategy under uncertainty in the lifetime distribution

Abstract

The problem of determining the optimal maintenance strategy for a machine given its lifetime distribution has been studied extensively. Solutions to this problem are outlined in the academic literature, prescribed in professional handbooks, implemented in reliability engineering software systems and widely used in practice. These solutions typically assume that the lifetime distribution and its parameter values are known with certainty, although this is usually not the case in practice. In this paper we study the effect of parameter uncertainty on the optimum age-based maintenance strategy. The effect of uncertainty is evaluated by considering both a theoretical uniform lifetime distribution and a more realistic Weibull lifetime distribution. The results show that admitting to the uncertainty does influence the optimal maintenance age and also provides a quantifiable cost benefit. The results can help maintenance managers in making maintenance decisions under uncertainty, and also in deciding when it is worthwhile to invest in advanced data improvement procedures.

Maintenance strategy decision for avionics system based on cognitive uncertainty information processing

“…Recent literature in aircraft maintenance safety tends to accept that deviations, uncertainties and surprises are inherent and to a large extent inevitable in maintenance operations [10,23,4]. In the process of avionics systems equipment maintenance, some judgments from maintenance experts or engineers may not be (fully) compatible due to lack of knowledge of the actual use and maintenance of the equipment.…”

“…where, 1 c is indicator of system safety, 2 c is Reliability, 3 c is Maintainability, 4 c is maintenance economy, 5 c is availability.…”

“…According to statistics, only 60% of the aircraft total failure can be found with ground inspection, while 40% of the fault is exposed during flight [5]. It is obvious that the integrity of the aircraft with a high rate is difficult to guarantee only with the ground inspection, but due to bad maintenance such as frequent power-on check or ineffective removal of equipment will cause the equipment to reduce the inherent reliability and waste the human and financial resources.Recent literature in aircraft maintenance safety tends to accept that deviations, uncertainties and surprises are inherent and to a large extent inevitable in maintenance operations [10,23,4]. In the process of avionics systems equipment maintenance, some judgments from maintenance experts or engineers may not be (fully) compatible due to lack of knowledge of the actual use and maintenance of the equipment.…”

Optimum Maintenance Policy for Equipment over Changing of the Operation Environment

“…However, Coolen and his coauthors [9,10] showed that this assumption impacts clearly the optimal replacement age and its cost per unit of time when the equipments undergo an age replacement policy (ARP). Recently in [11], de Jonge et al pointed out also the weakness of the assumption on knowing of the equipment lifetime distribution and proposed a parametric modeling of ARP for new equipment with an uncertainty on the parameters of the equipment lifetime distribution. In this work, de Jonge and his coauthors used Bayesian approach to model the uncertainty on the parameters and figured out that this uncertainty has effects on the optimal policy (age and cost) under ARP.…”

Zen and the Art of Railway Maintenance

“…An important element of accurate modelling of the system, is the decision of which probability distributions to use for the degradation rates of the components. This has been shown to have a major impact on the optimal maintenance policy and the total maintenance cost [dJKTT15]. FMTs support arbitrary probability distributions, allowing modellers to choose the most appropriate one, or experiment with different distributions to examine how much the choice impacts the results.…”