Modelling, Simulation and Fuzzy Decision Making of Distributed Production Control and Supply Chain Methodologies

Dieter Roller and Erik Engesser


Industrial control systems, modelling and simulation, global supply chain, fuzzy decision making


Distributed industrial production plants have to be managed by production planning and controlling (PPC) systems and enterprise resource planning (ERP) systems. Due to the globalization the PPC and ERP systems are supported by global supply chains controlled by supply chain management (SCM) systems. Various process methodologies exist for PPC, ERP and SCM systems. The research objective is to evaluate various distributed production and global supply chain process models. An approach is to use existing CAD information of development, production and supply chain planning and evaluate various process methodologies. The approach of this paper is to load existing CAD data into the application PROCAS (Process Optimization, Control, Analysis and Simulation). PROCAS was developed to design, simulate, optimize, evaluate and analyse process models for production planning, production control and supply chains. The approach of PROCAS is to design Business Process Modelling Notation (BPMN) models. The BPMN models can be transformed to petri net simulation models. Various methodologies can be evaluated by Fuzzy decision making (FDM). The fuzzy TOPSIS technique (Technique for Order Preference by Similarity to Ideal Solution) is used for finding the ideal solution between various alternatives and fuzzy criteria.

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