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MODELLING, SIMU LATION AND FUZZY DECISION MAKING OF DISTRIBUTED PRODUCTION CONTROL AND SUPPLY CHAIN METHODOLOGIES

机译:分布式生产控制与供应链方法的建模,拟模和模糊决策

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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.
机译:分布式工业生产设备必须通过生产计划和控制(PPC)系统和企业资源规划(ERP)系统来管理。由于全球化,PPC和ERP系统由供应链管理(SCM)系统控制的全球供应链支持。 PPC,ERP和SCM系统存在各种过程方法。研究目标是评估各种分布式生产和全球供应链流程模型。一种方法是使用现有的开发,生产和供应链规划的CAD信息,并评估各种过程方法。本文的方法是将现有的CAD数据加载到应用程序PROCA(过程优化,控制,分析和仿真)中。 PROCAS开发设计,模拟,优化,评估和分析生产计划,生产控制和供应链的过程模型。 ProCA的方法是设计业务流程建模符号(BPMN)模型。 BPMN型号可以转换为Petri网络仿真模型。通过模糊决策(FDM)可以评估各种方法。模糊TOPSIS技术(通过相似性与理想解决方案的顺序偏好技术)用于在各种替代品和模糊标准之间找到理想的解决方案。

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