Bayesian Statistical Method Enhance the Decision-Making for Imperfect Preventive Maintenance with a Hybrid Competing Failure Mode

The study aims to provide a Bayesian statistical method with natural conjugate for facilities’ preventive maintenance scheduling related the hybrid competing failure mode. An effective strategy not only can improve system’s health condition but also increase efficiency, and therefore firm needs make an appropriate increasing utilization of system reasonable costs. In last decades, issues deteriorating systems have been studied in literature, hundreds maintenance/replacement models created. However, few studies focused on issue which are composed maintainable non-maintainable modes. Moreover, due situations scarcity historical data, analyses would be difficult perform. Based above two reasons, this proposed deal such problems. Non-homogeneous Poisson processes (NHPP) power law intensity functions employed describe deterioration behavior. Accordingly, useful ways help managers decisions maintenance. To apply actual cases, provides solution algorithms computerized architecture design decision-makers realize computerization decision-making.