Degradation principle of machines influenced by maintenance

Abstract

Maintenance is important for the service of products and it is different from repair because repair focuses on the time node when the products break down, which is a qualitative problem, but maintenance pays more attention to the continuity of machine’s work, and thus it is not a qualitative problem. Nevertheless, almost all the study methods are of qualitative methods because they only qualitatively divided the health state of machines into several levels, which are not fit to comprehensively explore the degradation principle of machines and the relationship between degradation and maintenance. To discover the degradation principle of machines influenced by maintenance, a quantitative study method is proposed by calculating the Health Index (HI) based on fuzzy analytic hierarchy process (FAHP) and convolutional neural network (CNN). Finally, a case study is used to demonstrate the implementation and potential applications of the proposed method, in which two major maintenance methods in prognostic and health management (PHM), i.e. time-based maintenance (TBM) and condition-based maintenance (CBM) are studied. The results show that the application of the proposed method leads to a significant increase in the life of machines. This study puts forward a new method to study the degradation principle of machines and will lead to the development of PHM using the HI.