Design and Optimization of Smart Factory Control System Based on Digital Twin System Model

Abstract

Aiming at the problems of irrational allocation of resources, low efficiency caused by unbalanced production line layout, and slow production line upgrade of the smart factory, this paper builds a real physical smart factory platform through the optimal control strategy and uses the GRAFCET algorithm to optimize the logistics scheduling during the actual system operation. The genetic algorithm is used to optimize the layout effect of the production line; the digital twin technology is used to provide predictive analysis technical support for the upgrading and reengineering of the production line. Through the analysis and comparison of the production capacity and equipment utilization of the physical smart factory and the virtual smart factory processing scheme, practice shows that the design of the digital twin system can effectively improve the effect and accuracy of the lean production method in the production process reorganization. Quantitative analysis of manufacturing industry provides powerful theoretical and technical support.

[Retracted] Urban Road Landscape Design and Digital Twin Simulation Modeling Analysis

“…As a follow-up, the framework of digital twinbased equipment layout optimization is presented, in which real-time data collection and value addition are used to make layout decisions. Real-world smart manufacturing platforms are built using optimum control strategies and the GRAF-CET algorithm to optimize logistics scheduling during system operation in this work [9]. Production lines are optimized using a genetic algorithm, and digital twins are employed to give predictive analysis technical help for upgrading and reengineering [10].…”

Analysis and Detection of Transmission Lines Based on Twin Reality

“…Wang and Wu [17] built a digital twinbased projecting system model to manage and control uncertain factors in workshop scheduling. Bai et al [18] built a real physical intelligent factory platform based on digital twin technology, optimized the layout effect of production lines using genetic algorithms, and effectively improved the effect and accuracy of lean production. Bedir and Cor [19] proposed a pattern oriented near to the design of digital twin systems to build digital twin systems.…”

Cost-Optimal Pathfinding Model for Multi-Echelon Logistics Network Design and Optimization: A Fourth-Party Logistics (4PL) Perspective

“…In a construction logistics context, Lee and Lee leveraged real-time data from building information modeling (BIM) and geographic information system (GIS) to identify potential logistical risks and optimize routes [23]. For computational aspects, Bai et al proposed a genetic algorithm for the control system of a holistic factory production line environment inclusive of logistical processes and routes to increase efficiency based on lean production theory [24]. Pan et al presented a production logistics system utilizing multidisciplinary design optimization methods such as collaborative optimization and heuristics optimization algorithms to improve cost and production efficiency [25].…”