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

Abstract

With the boosting development of the advanced manufacturing industry in the world, the original production pattern transformed from the traditional industries into the intelligence mode is completed with the least delay possible, which are still facing new challenges. The timeliness, stability, and reliability of them are significantly restricted due to the lack of real-time communication. Therefore, a model framework of intelligent workshop manufacturing system based on a digital twin is proposed in this paper, driving the deep information integration among the physical entity, data collection, and information decision-making. The traditional digital twin of conceptualization and fuzziness needs to be refined, optimized, and upgraded on the basis of the four-dimension collaborative model thinking. The model framework of a refined nine-layer intelligent digital twin is established. Firstly, the physical evaluation is refined into entity layer, auxiliary layer, and interface layer, scientific managing the physical resources and 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 the production cycle, and reducing logistics cost. Simultaneously, combining SLP and artificial bee colonies is 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%.