Machine learning techniques applied to mechanical fault diagnosis and fault prognosis in the context of real industrial manufacturing use-cases: a systematic literature review

• Published in: Applied intelligence (Dordrecht, Netherlands) Vol. 52; no. 12; pp. 14246 - 14280
• Main Authors: Fernandes, Marta, Corchado, Juan Manuel, Marreiros, Goreti
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.09.2022; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Artificial neural networks; Computer Science; Decision trees; Digital systems; Distance learning; Fault detection; Fault diagnosis; Libraries; Literature reviews; Machine learning; Machines; Manufacturing; Mechanical Engineering; Predictive maintenance; Processes; Prognosis; Industrial case-study; Fault detection; Machine learning; Fault prognosis; Predictive maintenance; Manufacturing industry

When put into practice in the real world, predictive maintenance presents a set of challenges for fault detection and prognosis that are often overlooked in studies validated with data from controlled experiments, or numeric simulations. For this reason, this study aims to review the recent advancem...