Predictive Maintenance System for CNC Machines

The present invention relates to BE SHIELD, a state-of-the-art preventive maintenance system specifically designed for CNC machines in the hardware manufacturing industry. This invention addresses a critical niche, improving the operational efficiency and reliability of industrial machinery through advanced predictive maintenance. It comprises an integrated sensor kit installed on a CNC machine, equipped with various sensors, including temperature, pressure, and vibration sensors. The real-time data collected by these sensors is transmitted to a maintenance software. This software employs a sophisticated artificial intelligence model to monitor and analyses parameter trends continuously. By accurately predicting potential breakdowns in advance, this invention allows for timely pre-emptive actions, significantly reducing the risk of unexpected machine failures, downtime, and maintenance costs. In an industry, where expert maintenance personnel are not always readily available, this invention offers a substantial advantage. It ensures that experts can be scheduled proactively, thus enhancing the overall efficiency and productivity of manufacturing operations.

Authors

Institutions

Publication Details

Published
2025-05-01
DOI
https://doi.org/10.1109/iceccc65144.2025.11064291
Primary Topic
Engineering Diagnostics and Reliability
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predictive Maintenance System for CNC Machines

Merin Jacob, N Jayajevaa, S. Sridevi, S R Deeksha et al.
Engineering Diagnostics and Reliability
article

Predictive Maintenance System for CNC Machines

Merin Jacob, N Jayajevaa, S. Sridevi, S R Deeksha, R Ramya
article en

Abstract

The present invention relates to BE SHIELD, a state-of-the-art preventive maintenance system specifically designed for CNC machines in the hardware manufacturing industry. This invention addresses a critical niche, improving the operational efficiency and reliability of industrial machinery through advanced predictive maintenance. It comprises an integrated sensor kit installed on a CNC machine, equipped with various sensors, including temperature, pressure, and vibration sensors. The real-time data collected by these sensors is transmitted to a maintenance software. This software employs a sophisticated artificial intelligence model to monitor and analyses parameter trends continuously. By accurately predicting potential breakdowns in advance, this invention allows for timely pre-emptive actions, significantly reducing the risk of unexpected machine failures, downtime, and maintenance costs. In an industry, where expert maintenance personnel are not always readily available, this invention offers a substantial advantage. It ensures that experts can be scheduled proactively, thus enhancing the overall efficiency and productivity of manufacturing operations.

CMR University (IN)
Affordable and clean energy
Openalex Percentile: Top 81%
Engineering Diagnostics and Reliability
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.

Predictive Maintenance System for CNC Machines — Merin Jacob, N Jayajevaa, et al. · (2025) | TGRS Research Map | TGRS