Cost-benefit and reliability analysis of prognostic health management systems using fuzzy rules

Prognostic Health Management (PHM) systems have been found to be profitable in most industrial ventures as compared to Time-based Maintenance (TBM) or Corrective Maintenance (CM). However, while undertaking a Cost-Benefit Analysis (CBA), the profit obtained for a PHM system cannot be accurately known in all cases due to the vagueness present in certain parameters involved in the analysis. Our paper focuses on modeling the vagueness or uncertainty in these quantities using Fuzzy Rule-Based Systems (FRBS). Reliability being a major desirable objective, the influence of the quality of PHM on reliability analysis has been outlined. Fuzzy rules have also been employed considering both tangible and intangible benefits to present an accurate comprehensive model of the overall benefit. To evaluate the practicality of the cost-benefit analysis, an optimization condition has been derived, maximizing net benefit for given constraints. Over and above this analysis, how far the PHM system is advisable is determined by computing the risk factor associated with a PHM venture.