Author Login IJIRT Partner Network (IPN) Login

Strategic Predictive Maintenance Using XG Boost

  • Unique Paper ID: 164243
  • Volume: 10
  • Issue: 12
  • PageNo: 495-497
  • Abstract:
  • Predictive maintenance is a data-driven approach that uses predictive modelling to assess the state of equipment and determine the optimal timing for maintenance activities. This technique is particularly advantageous for industries heavily reliant on equipment for their operations, such as manufacturing, transportation, energy, and healthcare. Predictive maintenance (PdM) uses data analysis to identify operational anomalies and potential equipment defects, enabling timely repairs before failures occur. It aims to minimize maintenance frequency, avoiding unplanned outages and unnecessary preventive maintenance costs. By implementing a predictive maintenance solution with Python and XGboost, we can proactively identify and address issues to prevent costly downtime and ensure the smooth operation of our milling machines.
Download article email to a friend

Cite This Article

  • ISSN: 2349-6002
  • Volume: 10
  • Issue: 12
  • PageNo: 495-497

Strategic Predictive Maintenance Using XG Boost

Related Articles

Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

Join Our IPN

IJIRT Partner Network

Submit your research paper and those of your network (friends, colleagues, or peers) through your IPN account, and receive 800 INR for each paper that gets published.

Join Now

Latest Publication

Archive

View More

Recent Conferences

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024 Last Date: 15th March 2024

Submit inquiry