Identification of Key Machines in Complex Production Networks

The introduction of cyber-physical systems in production and logistics is a catalyst for a shift from centralized to decentralized production planning and control. However, equipping logistic objects (e.g. machines, products, transportation equipment) with the necessary technology is associated with high investment costs for companies. This paper presents a multiple attribute decision-making (MADM) method, which is suitable for identifying those machines of the production system, where an investment in technology for decentralized control leads to the largest increase in performance of the overall system. For this purpose production systems are modeled as complex networks, in which nodes represent machines and edges represent the material flow between them. Finally, we evaluate the performance of the proposed method taking a machine tool manufacturer with a job shop manufacturing as a research example.