Generic data structure and validation methodology for simulation of manufacturing systems

Gergely Popovics, András Pfeiffer, L. Monostori

Research output: Contribution to journalArticle

8 Citations (Scopus)


In recent years, the analysis and evaluation of manufacturing systems’ behaviour and their performance became essential. Discrete event simulation (DES) as a digital enterprise technology is an effective tool both in production related decision support processes and in structure or performance analysis of manufacturing systems. Building a DES model of a manufacturing system is a difficult task and requires special competence. Reducing the efforts spent on draft simulation is the aim of an ongoing research which is presented in the paper. The developed framework simplifies and accelerates the process of model building. A production oriented implementation of the ANSI/ISA-95 standard was used by the proposed modelling methodology to define a generic data structure supporting the creation of models without specific knowledge related to the simulation software applied. The data structure enables the development and application of proprietary simulation engines tailored for specific problems. On the other hand, numerous objective tests containing simulation model validation methods are also announced through a well-described example problem. By this method, several validating key performance indicators (KPIs) were tested, and it was indirectly determined whether the simulation model adequately represents the behaviour of the real system. The automatic simulation model generation in our approach enables using different simulation tools and presented through the examples of both commercial and self-developed software.

Original languageEnglish
Pages (from-to)1-15
Number of pages15
JournalInternational Journal of Computer Integrated Manufacturing
Publication statusAccepted/In press - May 28 2016



  • data structure
  • ISA 95
  • production simulation
  • self-building simulation
  • validation

ASJC Scopus subject areas

  • Computer Science Applications
  • Aerospace Engineering
  • Electrical and Electronic Engineering
  • Mechanical Engineering

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