Predictive Maintenance for Industrial Machinery using ML

Predicts equipment failure from vibration and temperature sensor time-series using a gradient-boosted survival model, giving maintenance teams a two-week failure-risk window.

Project code
AUX-MLR-1905
Domain
Machine Learning
Type
Software project
Level · Year
Advanced · 2025-26

Technologies and components

Machine LearningPythonXGBoostSensor Data

What is included

  • Complete source code
  • Database / dataset and setup guide
  • Project report (college format)
  • PPT for review and viva
  • Installation and demo support
  • Viva question guidance

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Frequently asked questions

Can I get the Predictive Maintenance for Industrial Machinery using ML project for my final year?

Yes. This project (code AUX-MLR-1905) is available as a software project kit for the 2025-26 academic year. Contact us on WhatsApp to request it.

Can this project be customised?

Yes. Features, technology and documentation can be modified to suit your guide and college requirements.

Which departments is this project suitable for?

CSE, IT, AI & DS, BCA and MCA students, and ECE students interested in software.

Get this project with full support

Ask about customisation, delivery time and viva support.

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