Construction of intelligent integrated model framework for the workshop manufacturing system via digital twin

Abstract

With the drastic development of the globally advanced manufacturing industry, transition of the original production pattern from traditional industries to advanced intelligence is completed with the least delay possible, which are still facing new challenges. Because the timeliness, stability and reliability of them is significantly restricted due to lack of the real-time communication. Therefore, an intelligent workshop manufacturing system model framework based on digital twin is proposed in this paper, driving the deep inform integration among the physical entity, data collection, and information decision-making. The conceptual and obscure of the traditional digital twin is refined, optimized, and upgraded on the basis of the four-dimension collaborative model thinking. A refined nine-layer intelligent digital twin model framework is established. Firstly, the physical evaluation is refined into entity layer, auxiliary layer and interface layer, scientifically managing the physical resources as well as the operation and maintenance of the instrument, and coordinating the overall system. Secondly, dividing the data evaluation into the data layer and the processing layer can greatly improve the flexible response-ability and ensure the synchronization of the real-time data. Finally, the system evaluation is subdivided into information layer, algorithm layer, scheduling layer, and functional layer, developing flexible manufacturing plan more reasonably, shortening production cycle, and reducing logistics cost. Simultaneously, combining SLP and artificial bee colony are applied to investigate the production system optimization of the textile workshop. The results indicate that the production efficiency of the optimized production system is increased by 34.46%.

Exploration and Reflection on the Construction of Intelligent Manufacturing Professional Clusters for Industrial Internet

“…Intelligent perception engineering trains applied engineering and technical personnel with the design and production of intelligent sensors, the design and manufacture of intelligent perception systems, application maintenance, operation and management, and other basic capabilities (Zhang & Liu, 2023). Intelligent manufacturing engineering cultivates high-quality applied engineering and technical talents in the field of intelligent manufacturing engineering who are engaged in the design of intelligent products and equipment, research and development of production lines, and the assembly, manufacture, application, and maintenance of intelligent equipment (Zhao et al, 2022). Industrial engineering, on the other hand, undertakes the cultivation of data management and analysis talents, who can grow up to become data analysis engineers, data mining engineers, data management engineers data product managers, etc (Zhou & Wei, 2022).…”

The architecture evolution of intelligent factory logistics digital twin from planning, implement to operation

“…Zhang et al 11 applied digital twin into Job shop scheduling problem to deal with the dynamic scheduling. Zhang et al 12 established a nine layered model framework of manufacturing system based on the digital twin. The proposed framework is based on the four-dimensional collaborative model and is refined into entity layer, auxiliary layer, interface layer, data layer, processing layer, information layer, algorithm layer, scheduling layer, and functional layer.…”

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

“…Marmolejo-saucedo developed a heuristics method based on vehicle routing and bin-packing problems to lower operational costs and optimize resources [27]. By combining a systematic layout design approach with an artificial bee colony algorithm within a textile manufacturer context, Zhang et al enhanced manufacturing flexibility, shortened production cycles, and reduced logistical costs [28].…”