With the continuous innovation of new-generation information technology and its accelerated integration with manufacturing industry, industrial internet platforms (IIPs) are rapidly emerging worldwide. Construction and application of IIP has become a new focus in international competition for leading enterprises, and also a new direction of industrial development for many countries worldwide. However, the development of IIP is still in the stage of exploration, and the industry sector still lacks unified understanding of the IIP. Therefore, this study firstly proposes a reference architecture of IIP to clarify its framework and core functions, so as to provide a general reference model for the industry to understand and jointly promote construction of IIP. Secondly, an assessment system is proposed to evaluate the usage of IIP. The assessment framework is composed from three domains namely the foundation, key capability, value and benefit. Finally, the practical value of the reference architecture and the assessment framework of IIP is verified by an industry practice.
Skilled operators are the most decisive key factors in manufacturing cells. An optimal assignment of operators is crucial for flexibility and productivity. Although there are many publications dealing with labor assignment problems, different forms of human cooperation on the shop floor and decentralized decision making, which are the main factors for system flexibility, are seldom concerned in existing models. In this article, a human‐oriented methodology to analyze, simulate, and evaluate labor assignment flexibility in changeover processes in manufacturing cells is introduced, which is characterized by an agent‐based approach. First, the problem architecture is presented along with the concepts of labor flexibility. Then, different types of human behavior in the changeover process are modeled. Furthermore, a human–machine interaction model is developed to integrate the human agent models into a generalized discrete event dynamic system (DEDS) process model. In this way, work process dynamics and cooperative behavior can be explicitly modeled and simulated. Third, the model is verified on the basis of a motorcycle engine manufacturing cell, and simulation experiments with different labor assignment schemes are designed and conducted. The simulation results show that assignment strategies incorporating different skill levels and cooperation styles have a significant impact on system performance. The agent‐based approach in conjunction with the human–machine interaction model can be used to analyze and solve a large class of assignment problems in flexible manufacturing systems, especially when human cooperation and collaboration are key factors shaping overall system performance.
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