Conceptualisation of a novel technique to incorporate artificial intelligence in preventive and predictive maintenance in tandem. (2022)

• Record Type: Journal Article
• Authors: Paul, Amrit Raj; Biswas, Shatarupa; Mukherjee, Manidipto
• Is Part Of: Materials today. Volume 66:Part 9(2022)
• Page Start: 3814
• Page End: 3821
• Publication Date: 2022
• Subjects: Predictive maintenance -- Preventive maintenance -- RNN -- Productivity -- Real-time data; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2022.06.250
• Languages: English
• ISSNs: 2214-7853

Abstract

Graphical abstract: Abstract: The maintenance of industrial machinery plays an important role to ensure the continuity of operation and productivity. Prediction of machine life-cycle and ensuring machine's health condition with the real-time data is difficult and non-productive with human indulgence. Moreover, available literature only focused on a single type of maintenance problem (either predictive or preventive) which further creates the bottlenecks in the maintenance system. The present article demonstrates the concept of a novel technique to conjugate the preventive and predictive maintenance using a recurrent neural network (RNN) based machine learning approach by incorporating real-time data physical data from the machines.