Cyber Physical Systems and Digital Twins

This module covers the general terminology and concepts related to cyber- physical systems and digital twins.

STARTING DATE: Spring 2022

Cyber-Physical Systems (CPS) can be defined as systems composed of collaborating computational entities which are in intensive connection with the surrounding physical world and its on-going processes, providing and using data-accessing and data-processing services available on the internet, at the same time (Monostori 2014), with the realization of the increasing importance of the interactions between interconnected computing systems and the physical world (Wang, Törngren & Onori 2016).

In this sense, Cyber-Physical Production Systems (CPPS) can be understood as systems that consist of autonomous and cooperative elements/sub-systems that are getting into connection with each other in situation-dependent ways, on and across all levels of production, from processes, production lines, to logistics networks.

As pointed out by Monostori (2014), modelling the operation of CPPS and also predicting their emergent behaviour raises a series of basic and application-oriented research tasks. Above all, integration of analytical and simulation-based models to their physical counterparts, i.e., Digital Twins (DT), can be projected to become more significant than ever in future industrial applications.

Learning objectives

  • Recognize and explain the terminology for key concepts and technologies of CPS and DT within the context of Industry 4.0.
  • Understand the state-of-the-art of DT for the process/cell/line level engineering and their possible uses for verification, analysis and optimization.
  • Describe different CPS and DT applications scenarios in manufacturing.
  • Through a survey and review, propose a possible application of CPS and DT in industry.

Module structure

The learning module is a mixture of self-study, webinars, and cross-company exercises.


Five themes covering:

  • Key enabling technologies for CPS
  • Virtual Commissioning
  • Virtual Robotics
  • Simulation-based Optimization for Digital Twins
  • Industrial applications of CPS and DTs

Expect videos, exercises, reflections that you share with other participants, forums for cross-participant discussions, and much more.

Time commitment

To complete this module, the participant is expected to schedule approximately 4 hours per week over 5 weeks (20 hours in total).

The schedule

Spring 2022 — The module starts
TBD — Virtual Commissioning Workshop
TBD — Discussion Forum


After applying to the program, please secure dates in your calendar to be able to join planned webinars and assure time available required for learning.

A unique module created in academia

This module is developed by Prof. Amos Ng from University of Skövde.

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