Modeling failure and maintenance effects of a system subject to multiple preventive maintenance types

摘要

Canada's mining sector contributed $54 billion to its GDP in 2013. Mining operations are an important element of Canada's economy and rely heavily on mobile equipment for the transportation of rock-ore. Failure of mobile equipment, when it is required to be in available state prevents the successful flow of mining operations, and can result in production losses averaging in millions of tons, annually. Consequently, the availability ??? and by extension, reliability ??? of mobile equipment have a direct economic impact on mine productivity. A mobile equipment's failures are the greatest contributors to its unavailability ??? and are observed to occur randomly. Typically, to help diagnose and curb mobile equipment failures, corrective and preventive maintenance policies are implemented. Maintenance personnel are concerned with quantifying the effect of multiple preventive maintenance policies on mobile equipment reliability and availability. Generally, this is performed by modelling the reliability of repairable systems. In most studies, it is assumed that repairable systems are subject to only one type of repair/maintenance, and the effect of repair/maintenance is captured using a single repair factor in an age reduction or intensity reduction model. In this paper, we consider a repairable system whose failures follow a Non-Homogenous Poisson Process, and the system is subject to corrective and several types of preventive maintenance. While the effect of corrective maintenance is minimal, a preventive maintenance may reduce the age of the system effectively. We assume different effects for different preventive maintenance types, and develop the likelihood function to estimate the failure process and preventive maintenance effects, simultaneously. We also derive the conditional reliability and the expected number of failures between two consecutive preventive maintenance types. The proposed methods are applied to a case study of two trucks used in a mining site. T- e proposed methods provide excellent predictions with the potential of becoming very useful in practice and of leading to further generalizations of repairable systems analyses.