Industrial Digital Transformation: Digital Twins and Predictive Maintenance


Industry 4.0 is an umbrella term that comprises a wide range of subjects, technologies and initiatives with a common thread: the use of information and communication technologies in the different industries (extractive, manufacturing, transport, utilities).

In the first part of this session, we will show the role of Simulink models and their simulations for:

  • Virtual Commissioning, accelerating and de-risking commissioning
  • the development of Digital Twins, which are virtual assets continuously fitted to the present state of the actual physical asset thanks to live data enabled by IoT

In the second part of this event, we will show how MATLAB enables the development of monitoring and classification algorithms for Predictive Maintenance applications, based on synthetic data provided by a Digital Twin built with Simulink due to the lack of enough failure data from the actual machine.

We will also show how to deploy one of those algorithms onto an edge device, in this case a PLC


  • Synthetic failure data generation from digital twins developed in Simulink
  • Data preprocessing and feature extraction in MATLAB
  • Failure root cause identification algorithm development
  • Remaining useful life (RUL) prediction algorithm development
  • Algorithm 


Time Title


Welcome and Introduction


Digital Transformation and Industry 4.0: Opportunities, Challenges and Solutions for Product Development


Simulink as a Platform for Modeling & Simulation of Virtual Systems

  • For system design
  • Digital Twins




IoT and the Power of Data

  • Update controllers
  • Predictive Maintenance
    • Failure Classification Algorithms
    • Remaining Useful Life estimation
  • Deployment to Edge Devices


Q&A and wrap-up

Product Focus

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