Institut für Automatisierungstechnik

Model-based Dependability Analysis for Mechatronic Systems

ET-12 01 11 
WF 1/1/0 
Dr.-Ing. A. Morozov 

LV Model-based Dependability Analysis for Mechatronic Systems (SS2020)

17:00 Uhr @ online 

--> Downloads siehe OPAL 

Goal of the course (Ziel des Lehrfaches)

Model-based System Engineering (MBSE) is widely accepted in a variety of safety-critical industrial domains including aerospace and industrial automation. Recent trends in technology, such as Industry 4.0, Cyber-Physical Systems, and Internet-of-Things significantly increase the interest of this topic. MBSE implies an automated process of system development from semi-formal system specification up to final implementation. MBSE is supported with software for the formulation of system requirements, detailed design, and even automated implementation. This helps both to simplify and speed up system development and provide information for earlier system analysis. Modern standards for high-tech software and hardware systems demand the high level of dependability properties (such as reliability, safety, security) that cannot be achieved without the thorough comprehension of structural and behavioral aspects of these highly heterogeneous systems and their components. This course provides an overview of modern MBSE approaches (UML/SysML, Simulink, AADL), key dependability metrics (MTTF, Failure rate), classical reliability and safety evaluation methods (FTA, FMEA), as well advanced methods data error propagation and timing analysis based on stochastic probabilistic models such as Markov Chains and Stochastic Petri Nets.

Content of the course (Inhalt des Lehrfaches)

8 Lectures + 4 Exercises + Project


  • Safety-critical mechatronic and Cyber-Physical Systems (CPS), model-based system engineering
  • Dependability theory (reliability, safety, security, resilience)
  • Metrics and method for reliability and safety analysis (RBD, ETA, FTA, FMEA)
  • Fault tolerance and anomaly detection techniques
  • Model checking and stochastic models (Markov Chains, Stochastic Petri Nets)
  • Data error propagation analysis
  • Timing analysis of distributed components ?
  • Key challenges of analytical and simulative approaches


  • Model-based design of a mechatronic system (SysML or AADL)
  • Fault tolerance and reliability analysis (Static and Dynamic Fault Trees)
  • Analysis of data errors propagation (ErrorPro)
  • Analysis of timing errors (Stochastic Model Checking)


Each group (2-3 students) designs a model of a simplified mechatronic system and performs model-based dependability analysis using the methods introduced in the lectures and demonstrated in the exercises. Each group will make a 15 minutes' final presentation.

Prior knowledge:

Basics of system Design, Finite State Machines, Petri Nets, UML (recommended) xxx

Stand: 20.04.2020 08:23
Autor: Webmaster IFA