The use of artificial neural network models to enrich the analytical and predictive capabilities
of decision support systems in manufacturing has increased. The growing complexity and …

Composite materials are those formed by combining two or more different materials to take
advantage of the best characteristics of each one. However, due to this heterogeneity …

Fault detection and diagnosis in time series data are becoming mainstream in most
industrial applications since the increase of monitoring sensors in machinery. Traditional …

Centrifugal pumps are an integral part of many industrial processes and are used
extensively in water supply, sewage, heating and cooling systems. While there are several …

Monitoring the condition of unreachable gears of epicyclic gearbox in real-time increases
the asset reliability by anticipating the failures through preventive maintenance. Machine …

Abstract Industry 4.0 denotes smart manufacturing, where rotating machines predominantly
serve as the fundamental components in production sectors. The primary duty of …

In fault diagnosis, machine learning theories are gaining popularity as they proved to be an
efficient tool that not only reduces human effort but also identifies the health conditions of the …

To simultaneously monitor some electrical or mechanical faults of an in-wheel motor and
intelligently evaluate the operation safety, in this article, a fuzzy system of operation safety …

Purpose Fault diagnosis is vital to any maintenance sector since early fault detection can
avoid catastrophic failures and also a waste of both time and money. Common defect …

The fault prediction and abductive fault diagnosis of three‐phase induction motors are of
great importance for improving their working safety, reliability, and economy; however, it is …