Predictive Maintenance with MATLAB: A Prognostics Case Study


Overview

Predictive maintenance reduces operational costs for organizations running and manufacturing expensive equipment by predicting failures from sensor data. In this talk, we will learn how MATLAB® and Predictive Maintenance Toolbox™ combine machine learning with signal processing techniques for predicting failures.

This webinar will focus on the workflow for estimating remaining useful life of machines by preprocessing, extracting, visualizing , and selecting trendable features from sensor data. The trendable sensors are used to construct a Similarity based RUL Estimator. 

Highlights

  • Predictive Maintenance Overview and Workflow
  • Overview of Machine Learning Techniques
  • RUL Methods and when to use them
  • Constructing a health indicator
  • Demo - RUL Estimation of Turbo Fan Engine  
  • Q&A

Who Should Attend

Researchers, PhD, Masters students, other academics and engineers interested in Predictive Maintenance.  

About the Presenter

Rohit Agrawal
Senior Customer Success Engineer, MathWorks 

Product Focus

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