An optimal condition based maintenance strategy using inverse-Gaussian degradation process

Abstract

Condition based maintenance (CBM) is a practical and effective way to guarantee the product availability. Recent years the optimization strategy of CBM is widely studied by researchers. For product with measurable degradation performance, degradation modeling plays an important role in CBM. Inverse Gaussian process has many superb properties in dealing with covariates and random effect. In this paper, a new CBM optimization model is developed basing on the nonlinear inverse Gaussian degradation model. With the constraint of cost, the optimal CBM strategy is obtained by maximizing availability of product. Specifically, we consider imperfect preventive maintenance and proposed a way to describe its influence. Finally, the proposed model is demonstrated by a numerical example.