Ms. Seema Nagrani

Research Scholar, Department of Mechanical Engineering, K. J. Somaiya college of Engineering, Mumbai – 400 077. And Assistant Professor, Department of Mechanical Engineering, Thakur College of Engineering and Technology, Mumbai

Vaibhav S. Narwane

Associate Professor, Department of Mechanical Engineering, Somaiya Vidyavihar University, K.J. Somaiya College of Engineering, Vidyavihar, Mumbai – 400 077

Abstract

Predictive maintenance plays very important role in fourth revolution of Industry to improve the productivity and to reduce the maintenance cost. The Digital Twin model is used in design, manufacturing, and maintenance work. The main purpose of this study is to conduct systematic literature review on predictive maintenance using Digital Twin model. The research articles selected from year 2017 to 2023 and 46 articles are shortlisted for detailed study. The research articles are divided into three categories. The research articles help to find the relation between predictive maintenance, Digital Twins and Machine Learning algorithms. The study is limited to research articles from peered reviewed articles of reputed journals published in English. Book chapters, white papers and unpublished work are not considered for the study. This research article is one of the few articles which highlight the application of Digital Twins in Predictive Maintenance.

Keywords- Digital Twins, Predictive Maintenance, Machine Learning, Industry 4.0, vibration analysis, condition-based monitoring