Systematic Literature Review on Visual Analytics of Predictive Maintenance in the Manufacturing Industry

• Published in: Sensors (Basel, Switzerland) Vol. 22; no. 17; p. 6321
• Main Authors: Cheng, Xiang, Chaw, Jun Kit, Goh, Kam Meng, Ting, Tin Tin, Sahrani, Shafrida, Ahmad, Mohammad Nazir, Abdul Kadir, Rabiah, Ang, Mei Choo
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 23.08.2022; MDPI
• Subjects: Artificial Intelligence; Decision making; deep learning; Electric power production; Energy consumption; Energy efficiency; explainable artificial intelligence; Factories; Humans; industry 4.0; Information management; Literature reviews; Machine learning; Manufacturing; Manufacturing Industry; Mathematical programming; Optimization; predictive maintenance (PdM); Sensors; Subject specialists; Systematic Review; visual analytics; Visualization; Malaysia; explainable artificial intelligence; visual analytics; deep learning; machine learning; industry 4.0; predictive maintenance (PdM)

The widespread adoption of cyber-physical systems and other cutting-edge digital technology in manufacturing industry production facilities may motivate stakeholders to embrace the idea of Industry 4.0. Some industrial companies already have different sensors installed on their machines; however, wi...