Machine Learning Applications for Reliability Engineering: A Review

The treatment of big data as well the rapid improvement in speed processing are facilitated by parallelization computations, cloud computing increasing number artificial intelligence techniques. These developments lead to multiplication applications and modeling Reliability engineering includes several research areas such reliability, availability, maintainability, safety (RAMS); prognostics health management (PHM); asset (AM), aiming at realization life cycle value. expansion (AI) techniques combined with various topics increases difficulty practitioners identifying appropriate methodologies applicable. objective this publication is provide an overview different machine learning (ML) from perspective traditional Furthermore, it presents a methodology for science application how can be applied each step. Then, will demonstrate ML complementary approaches, cases literature presented.