Bibliometric Review of Predictive Maintenance using Vibration Analysis

Authors

Aashna Midha Ms., Symbiosis Institute of Technology, Symbiosis International (Deemed University)Follow
Ishita Maheshwari Ms., Symbiosis Institute of Technology, Symbiosis International (Deemed University)Follow
Kaushik Ojha Mr., Symbiosis Institute of Technology, Symbiosis International (Deemed University)Follow
Kritika Gupta Ms., Symbiosis Institute of Technology, Symbiosis International (Deemed University)Follow
Shripad V. Deshpande Mr., Symbiosis Institute of Technology, Symbiosis International (Deemed University)Follow

Date of this Version

Summer 5-31-2021

Abstract

Every day the world is depending more and more on machines in almost every aspect of life. With the increasing use of machines, there also needs to be an evolution in the maintenance of these machines. Predictive maintenance is a process used to monitor the equipment and machinery during its operation to detect any damages and/or deteriorations and enable the required maintenance plan in advance, resulting in reduced operational costs and full utilization of tools and parts. The fundamental goal of this bibliometric review paper is a comprehension of the extent and sources of the literature available for predictive maintenance systems. The bibliometric review is based on the Scopus database and data visualization tools like ScienceScape. The time series dataset considered is from 2006 to 12^th May 2021, as these years saw a rise in research in the field of predictive maintenance. The articles on Predictive Maintenance revealed a remarkable improvement that again emphasizes the importance of paper reviews. This research paper shows some significant analysis about the focus of research in this field and shows future perspectives and improvements for research in this field.