Predictive Reliability Modelling of an Industrial System

Arnab Naskar

Abstract: Across the industries, there is a growing need of increased Operational Reliability, Availability and Maintainability of the equipment, which comprises of diagnosis and prognosis of a particular problem. As systems are evolving daily to a new level of sophistication, maintenance of those systems needs a critical approach. Hence, more industries are trying to adapt predictive maintenance policies in their critical area of operations. With the advantage of predictive analytics and machine learning techniques, predictive maintenance is gaining its momentum in different industries. In this paper, a framework of predictive reliability modelling has been discussed, which is a part of predictive maintenance. With the help of various machine-learning models along with Deep Neural Network, one predictive reliability model has been made. This paper also projects a model to calculate Remaining useful life (RUL) by incorporating Recurrent Neural Network (RNN).

Keywords: Industry 40, Predictive Analytics, Machine Learning Techniques, Diagnosis, Prognosis, Predictive Maintenance, Reliability, Maintainability, Availability, Recurrent Neural Network

How to Cite?: Arnab Naskar, "Predictive Reliability Modelling of an Industrial System", Volume 9 Issue 9, September 2020, International Journal of Science and Research (IJSR), Pages: 1361-1364, https://www.ijsr.net/getabstract.php?paperid=SR20924175618, DOI: https://dx.doi.org/10.21275/SR20924175618