Research on preventive maintenance strategy of Coating Machine based on dynamic failure rate

In this paper, a dynamic preventive maintenance strategy is proposed for the problem of high cost rate due to excessive caused by unreasonable threshold setting when complex electromechanical equipment formulated. Increasing failure factor and decreasing service age are introduced describe evolution rules during coating machine, BP-LSTM (BP-Long Short Term Memory Network, BP-LSTM) model combined predict machine. A Dynamic Model (DM) that relies on thresholds classify three modes minor, medium major repairs constructed. optimization process based Genetic-Particle Swarm Optimization (GPSO) algorithm with lowest per unit time in phase built solve difficult finding. Based historical operating data case study machine was conducted verify effectiveness developed paper. The results show paper can ensure better economy applicability.