A Digital Twin-Assisted Collaborative Capability Optimization Model for Smart Manufacturing System Based on Elman-IVIF-TOPSIS

Abstract

Smart manufacturing is one of the key elements to realizing Industry 4.0, which helps to improve the production quality and efficiency of collaborative manufacturing companies. With the rapid development of information technology such as the Internet of Things, the application of digital twin technology in smart manufacturing is becoming more and more widespread. In the manufacturing process, companies still face problems such as slow data flow and a serious waste of idle equipment resources. The purpose of this paper is to carry out a digital twin-based smart manufacturing system that combines the concept of value co-creation to achieve the smart manufacturing goal of using fewer manufacturing resources to create greater system value. The system builds a multi-objective optimization model to enhance the value of the shared supply chain and then helps collaborative manufacturing enterprises to optimize their production capacity and use population intelligence algorithms to solve the problem. The results of the combined case study show that the system is effective in achieving good operation of dynamic equipment resources while improving the overall profit of the system by 13.26%. This study proposes a smart manufacturing system based on the digital twin and considering the value of the supply chain will effectively help collaborative manufacturing enterprises to respond to the market environment quickly, reduce the loss of manufacturing resources while also significantly reducing the operating costs of enterprises, and help to realize the value of the shared supply chain.