Abstract

Maintenance operations refer to the set of activities required to replace a component, or a group of components subjected to wear and tear in a system, asset or machine. Among such maintenance operations, preventive maintenance plays an important role for its proactive effect on the serviceability of components in a system. Scheduling of preventive maintenance is a critical operation in maintenance and reliability engineering which helps construct proactive programs to improve the operating condition of assets and extend their service life. In its general settings, the partners of an asset include (i) the asset vendor (ii) the asset user and (iii) the service maintenance provider. The most common rules in preventive maintenance is the assumption of constant failure rates, constant frequency of maintenance tasks that follows the mean time to failure models to a certain extent and “as-good-as-new” upon repair activities. While such assumptions focus on durability, however, they do not guarantee cost optimal solutions. In contrast to the above assumptions, the aim of this study is to present an original Mixed Integer Linear Programming model (MILP) of cost-based scheduling. Here, different resources and reliability functions will be considered in the model. The model also tends to reduce the overall cost function of spare parts contributions, the cost of implementing preventive measures and the cost of additional repair activities considering the staff efficiency that is monitored and controlled using latest efficient work monitoring technology. This proposed model is a part of PhD study at the University of Sharjah. The model is to be validated using real data and further comparisons will be considered as our research advances during our study.