The programme covers the following key topics:
Introduction of Data Analysis for Predictive Maintenance and Optimal Plan
- Introduction predictive maintenance in the age of Industrial 4.0
- Introduction of fundamental concepts of data analysis
- Issues in the data and methods of preparing data
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Case study: Data analysis for predictive maintenance
Data Processing and Modelling Techniques
- Data processing and modelling techniques for machine learning
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Issues in using imbalance data
- Oversampling techniques to handle imbalanced data
- Case study: Equipment health analysis using machine learning
PdM-enabled Maintenance Management System
- Introduction of PdM enabled maintenance management system
- Make use of integrated MMS dataset for predictive maintenance
- Architecture and system design for integrating MMS with ML engine
- Case Study and hands-on: MMS to collect data for predictive maintenance
Downtime Forecast and Optimal Maintenance Plan
- Models for Manufacturing Systems and Maintenance
- Optimal Forecasting Methods and Applications
- Optimal Maintenance Plan
Forecasting Tool and Hands-on
- Case Study: Production Line Downtime Forecast
Please register for this course under 1. Modular Programmes > 2. Data driven Predictive Maintenance and Optimal Plan in the online registration form.