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Nagdev Amruthnath edited this page Jan 11, 2019 · 2 revisions

Welcome to the Predictive-Maintenance wiki!

This project is aimed to provide a brief tutorial on different aspects of predictive maintenance. We will be mainly using tools such as R and Jupyter notebooks in this tutorial. This tutorial consists of for key areas we will be dealing and are as follows:

  1. Fault prediction
  2. Fault classification using supervised learning
  3. Fault classification using clustering
  4. Time to Failure Prediction
  5. (optional) factor analysis to perform root cause analysis

Some of the packages we will be using are caret and h2o to perform this analysis. Most of the code will be executable. But, I will not guarantee it. Also, use it responsibly.

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