To provide direction and advice for future research on Industry 4.0 maintenance, we
conducted a comprehensive analysis of 344 eligible journal papers published between …

Under the promotion of sustainable development goals, cleaner production (CP) has
become an important strategy for energy-intensive manufacturing industries to maintain their …

Recent years have witnessed prominent advances in predictive maintenance (PdM) for
complex industrial systems. However, the existing PdM literature predominately separates …

Fault diagnosis is efficient to improve the safety, reliability, and cost-effectiveness of
industrial machinery. Deep learning has been extensively investigated in fault diagnosis …

Remaining useful life (RUL) estimation has been intensively studied, given its important role
in prognostics and health management (PHM) of industry. Recently, data-driven structures …

Featured Application Maintaining production systems within Industry 4.0 facilitates the
application of artificial intelligence methods, techniques and tools to predict potential failures …

PHM technology is vital in industrial production and maintenance, identifying and predicting
potential equipment failures and damages. This enables proactive maintenance measures …

Abstract Researches on Remaining Useful Life (RUL) prediction of aero-engine could help
to make maintenance plans, improve operation reliabilities and reduce maintenance costs …

Although current deep learning models for bearing fault diagnosis have achieved excellent
accuracy, the lack of constraint-guided learning of the physical mechanisms of real bearing …

Accurate prediction of the remaining useful life (RUL) of rolling bearings is important to
ensure the safe operation of mechanical system and to formulate maintenance strategies …