A Revolutionary Journey on Modern Industrial Automation with Intelligent System Design on Fault Predection-

In present scenario a significant amount of the global GDP is being diverted towards maintenance, more commonly for acknowledging breakdown or equipment’s failure. Behavior of operation with favorable safety satisfied industrial basic expectation fulfilling industrial devices are in the range of its maximum potential of usefulness. The technology as M2M communication, Modern sensor technologies, associated with latest information technologies principle are more helpful on minimizing unused potential of equipment by providing real-time data on performance levels. On availability of such these input data a proper maintenance schedule can be develop to maintain the right parts with the right means without losing equipment efficiency. Hence predictive maintenance has a great role on industrial safety and smooth operation. This research article expresses the proper analyze of predictive maintenance features. as condition monitoring, fault diagnosis. Here all possible technology associated to predictive maintenance is considered and finally a suitable solution is given for better and early maintenance process. The objective of this research work is to analyze previous information so as to develop a system that would provide an alert message on the event of any unusual behavior of machines so that the maintenance can be done in advance through surveillance of the situation, information analysis.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-03-29
DOI
https://doi.org/10.52783/jisem.v10i27s.4374
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Revolutionary Journey on Modern Industrial Automation with Intelligent System Design on Fault Predection-

B. Sudhir
Journal of Information Systems Engineering & Management
Industrial Vision Systems and Defect Detection
article

A Revolutionary Journey on Modern Industrial Automation with Intelligent System Design on Fault Predection-

B. Sudhir
article en

Abstract

In present scenario a significant amount of the global GDP is being diverted towards maintenance, more commonly for acknowledging breakdown or equipment’s failure. Behavior of operation with favorable safety satisfied industrial basic expectation fulfilling industrial devices are in the range of its maximum potential of usefulness. The technology as M2M communication, Modern sensor technologies, associated with latest information technologies principle are more helpful on minimizing unused potential of equipment by providing real-time data on performance levels. On availability of such these input data a proper maintenance schedule can be develop to maintain the right parts with the right means without losing equipment efficiency. Hence predictive maintenance has a great role on industrial safety and smooth operation. This research article expresses the proper analyze of predictive maintenance features. as condition monitoring, fault diagnosis. Here all possible technology associated to predictive maintenance is considered and finally a suitable solution is given for better and early maintenance process. The objective of this research work is to analyze previous information so as to develop a system that would provide an alert message on the event of any unusual behavior of machines so that the maintenance can be done in advance through surveillance of the situation, information analysis.

Journal of Information Systems Engineering & ManagementVol. 10(27s)
Openalex Percentile: Top 92%
Industrial Vision Systems and Defect Detection
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.