Predictive maintenance is the most recent technique in maintenance engineering. Machine operational parameters are used to assess the health of equipment and decide on maintenance schedule. In Aviation, aircraft engine manufacturers continuously monitor their engine parameters in flight to evaluate performance and deviations from normal.

Application of AI in this field enables measurement of behavior that is not observable using traditional means. AI based monitoring provides the edge required to operate in Industry 4.0 where connected machines do away with buffers in between processes and any unscheduled downtime of one machine effects the entire production chain.

This demonstration will walk you through the development of AI models using IoT data for one of the largest metal manufacturing company in India. It will help you master different types of AI models to answer questions like

  • When do I plan the maintenance of a given equipment?
  • Will a component last till the next maintenance cycle or do I replace it during the current maintenance?
  • How to identify faulty equipment in the long production line?

Outline/Structure of the Demonstration

The demonstration is structured as follows

  • Brief introduction to maintenance techniques (2 mins)
  • Predictive maintenance - traditional approaches (2 mins)
  • AI models for machine health monitoring
    • Anomaly detection techniques for (6 mins)
      • Steady state operation - elliptic envelope & isolation forest
      • Varying load cycles - regression & boosting models
    • Time to failure / remaining useful life prediction - survival models & forecasting (5 mins)
    • Locating faulty equipment in a long process chain (3 mins)
  • More applications (2 mins)

Learning Outcome

As you participate in this demonstration, you will learn and master the skills required to build and deploy your own AI model for machine performance monitoring.

Target Audience

Practitioners in Industry 4.0, Internet of Things (IoT), Manufacturing, Reliability & Maintenance

Prerequisites for Attendees

Basic understanding of maintenance and reliability.


schedule Submitted 3 years ago