Because of their cross-functional nature in the company, enhancing Production Planning
and Control (PPC) functions can lead to a global improvement of manufacturing systems …

Wind energy farms are moving into deeper and more remote waters to benefit from
availability of more space for the installation of wind turbines as well as higher wind speed …

In recent years, advances in computer technology and the emergence of big data have
enabled deep learning to achieve impressive successes in bearing condition monitoring …

Fault diagnosis plays an important role in actual production activities. As large amounts of
data can be collected efficiently and economically, data-driven methods based on deep …

Remaining useful life (RUL) prediction, has been a hotspot topic in the engineering field,
which can ensure the security, availability, and continuous efficiency of the system. Different …

Fault diagnosis is useful in helping technicians detect, isolate, and identify faults, and
troubleshoot. Bayesian network (BN) is a probabilistic graphical model that effectively deals …

Fault diagnosis is important to ensure the safety and efficience of mechanical equipment. In
recent years, data-driven fault diagnosis methods have received extensive attention and …

Time-varying temperature condition has a significant impact on discharge capacity and
aging law of lithium-ion battery. Consequently, a novel remaining useful life (RUL) prediction …

Fault diagnosis with transfer learning has achieved great attention. However, existing
methods mostly focused on single-source-single-target sceneries. In some cases, there may …

Early identification of rolling element defects is always a topic of interest for researchers and
the industry. For early fault identification, a simple and effective dynamic degradation …