Specifying measurement errors for required lifetime estimation performance

Lifetime estimation based on the measured health monitoring data has long been investigated and applied in reliability and operational management communities and practices, such as planning maintenance schedules, logistic supports, and production planning. It is known that measurement error (ME) is a source of uncertainty in the measured data considerably affecting the performance of data driven lifetime estimation. While the effect of ME on the performance of data driven lifetime estimation models has been studied recently, a reversed problem—“the specification of the ME range to achieve a desirable lifetime estimation performance” has not been addressed. This problem is related to the usability of the measured health monitoring data for estimating the lifetime. In this paper, we deal with this problem and develop guidelines regarding the formulation of specification limits to the distribution-related ME characteristics. By referring to one widely applied Wiener process-based degradation model, permissible values for the ME bias and standard deviation can be given under a specified lifetime estimation requirement. If the performance of ME does not satisfy the permissible values, the desirable performance for lifetime estimation cannot be ensured by the measured health monitoring data. We further analyze the effect of ME on an age based replacement decision, which is one of the most common and popular maintenance policies in maintenance scheduling. Numerical examples and a case study are provided to illustrate the implementation procedure and usefulness of theoretical results.     

A preventive maintenance policy for a continuously monitored system with correlated wear indicators

A continuously monitored system is considered, that gradually and stochastically deteriorates according to a bivariate non-decreasing Lévy process. The system is considered as failed as soon as its bivariate deterioration level enters a failure zone, assumed to be an upper set. A preventive maintenance policy is proposed, which involves a delayed replacement, triggered by the reaching of some preventive zone for the system deterioration level. The preventive maintenance policy is assessed through a cost function on an infinite horizon time. The cost function is provided in full form, and tools are provided for its numerical computation. The influence of different parameters on the cost function is studied, both from a theoretical and/or numerical point of view.     

On a single discrete scale for preventive maintenance with two shock processes affecting a complex system

A new approach to optimal maintenance of systems (networks) is suggested. It is applied to systems subject to two external independent shock processes. A system ‘consists’ of two parts, and each shock process affects only its own part. A new notion of bivariate signature is suggested and used for obtaining survival characteristics of a system and further optimization of the preventive maintenance actions. The preventive maintenance optimization is considered in the univariate discrete scale that counts the overall numbers of shocks of both types. An example of a transportation network is considered. Copyright © 2016 John Wiley & Sons, Ltd.