Reliability Optimization of Uncertain Random Systems Combined With Burn-In and Preventive Maintenance

It is well-known that uncertain random systems suffered from a competing failure process have been applied in industrial applications. Extending previous studies, we optimize system cost combined with burn-in and preventive maintenance strategies. A system in burn-in process is only subject to uncertain continuous stationary degradation process while it experiences competitive degradation and shock processes simultaneously in the period of operation. The dependence assumes that shocks can accelerate the degradation by uncertain additional degradation shifts. A reliability optimization model for uncertain random systems is proposed where the reliability index is defined as a chance measure, and the optimal burn-in parameters and maintenance observation time are derived by the genetic algorithm. Finally, we conclude with a numerical example to illustrate the application of burn-in and maintenance methods.

Automated summary

This study combines system cost optimization with burn-in and preventive maintenance strategies for uncertain random systems affected by competing failure processes. The reliability optimization model proposes a chance-based reliability index, and the optimal burn-in parameters and maintenance observation time are derived using the genetic algorithm. A numerical example is provided to illustrate the application of burn-in and maintenance methods.