Model-based stochastic error propagation analysis for cyber-physical systems

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

Abstract

Industry 4.0 is the current trend of automation and data exchange in manufacturing technologies that is focusing on the creation of smart factories with the modular structured Cyber-Physical Systems (CPS), in tight cooperation with humans. This trend also implies that the systems become more complex, heterogeneous, and distributed especially their network and software parts. This makes the CPS highly critical subject to failures at different levels, including software, hardware, and human operators. Consequently, ensuring reliable and safe operation under the presence of non-avoidable threats also becomes a more complicated task. The proper analysis of the CPS requires thorough comprehension of both the dependability properties of system components and their interactions as well as structural and behavioral aspects of the complete system. Such an analysis of complex and mutually interlinked system properties puts considerable challenges on appropriate methods for modeling and analysis, as well as, on the related applied software tools. The Dual-graph Error Propagation Model (DEPM), developed in our lab, is a mathematical abstraction of the main future system’s properties, which are vital for the determination of the error propagation processes. It is a useful analytical instrument for the evaluation of the influence of particular faults and errors to the overall system behavior. OpenErrorPro is our analytical software tool for stochastic error propagation analysis that supports the DEPM framework. Using OpenErrorPro, a DTMC model could be automatically generated from a DEPM, and the reliability metrics, in addition to, error propagation path, can be computed. This could be implemented for the analysis of the heterogeneous CPS components. The necessary steps for the DEPM framework extension, required for such an implementation, are discussed in this paper.

Details

Original languageEnglish
Pages (from-to)15-28
Number of pages14
JournalActa polytechnica hungarica : journal of applied sciences
Volume17
Issue number8
Publication statusPublished - 2020
Peer-reviewedYes

Keywords

ASJC Scopus subject areas

Keywords

  • Control flow, Cyber-Physical System, Data flow, Dependability, Error propagation model, Industry 4.0, Markov chain model, Model-based analysis, Model-based system, Optimization, Probabilistic Model Checking, Reliability, Safety