A Survey of Model-Based System Engineering Methods to Analyse Complex Supply Chains: A Case Study in Semiconductor Supply Chain

Abstract Model-Based System Engineering (MBSE) is an increasingly important methodology to support system engineering and has attained a high level of attentiveness in business simulation practices as a conceptual modelling approach. In this paper, we present our results related to the application of MBSE approaches in complex semiconductor manufacturing supply chain planning systems. We investigate System Modeling Language (SysML), Web Ontology Language (OWL) and Business Process Modeling Notation (BPMN) as different approaches and languages for MBSE. These approaches are surveyed and used to develop conceptual models for the simulation of the order management process inside the supply chain management. This study aims to survey and offer a number of implications for MBSE practice and seeks to stimulate and guide further research in this area.

[1]  Stefan Feldmann,et al.  Combining a SysML-based Modeling Approach and Semantic Technologies for Analyzing Change Influences in Manufacturing Plant Models☆ , 2014 .

[2]  Armando Calabrese,et al.  A BPMN extension to support discrete-event simulation for healthcare applications: an explicit representation of queues, attributes and data-driven decision points , 2018, J. Oper. Res. Soc..

[3]  Erik Herzog,et al.  2.3.1 SysML – an Assessment , 2005 .

[4]  Thomas R. Gruber,et al.  A translation approach to portable ontology specifications , 1993, Knowl. Acquis..

[5]  Alexander Seitz,et al.  Increasing accuracy and robustness of order promises , 2017, Int. J. Prod. Res..

[6]  Marko A. Hofmann,et al.  Epistemic and normative aspects of ontologies in modelling and simulation , 2011, J. Simulation.

[7]  Brian Willard.  UML for systems engineering , 2007, Comput. Stand. Interfaces.

[8]  James D. Arthur,et al.  Investigating the use of software requirements engineering techniques in simulation modelling , 2007, J. Simulation.

[9]  Con Sheahan,et al.  Development and construction of an ontology to represent simulation data for a generic enterprise , 2010, Appl. Ontology.

[10]  Dieter Fensel,et al.  Knowledge Engineering: Principles and Methods , 1998, Data Knowl. Eng..

[11]  Leon F. McGinnis,et al.  Ontologies and simulation: a practical approach , 2011, J. Simulation.

[12]  Alberto Trombetta,et al.  BPMN: An introduction to the standard , 2012, Comput. Stand. Interfaces.