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Industry 4.0 focuses on the realization of smart manufacturing from shop floors to factories and to the whole supply chain. As a key technology of smart manufacturing, cyber-physical system has been widely discussed in the aspects of system design, data collection and processing, and cyber-physical synchronization. In a smart shop floor, manufacturing resources with intelligence and autonomy are abstracted as cyber-physical system units. They can communicate with each other autonomously to make optimal production decisions according to the real-time status of the shop floor. In this article, an autonomous collaboration network comprised of cyber-physical system–based smart manufacturing resources is modeled by using complex network theory. The collaboration activities among them are further analyzed, from which the information of key cyber-physical system units and key collaboration relationships are excavated. A demonstrative case is studied to verify the feasibility of the proposed model. From the case, it can be seen that (1) autonomous collaboration network has a small-world feature; (2) cyber-physical system units with bigger degrees and the collaborative relationships with bigger tightness are more important; (3) the workload of cyber-physical system units needs to be balanced because some cyber-physical system units have exceeded their capacities; and (4) cyber-physical system units with larger collaboration clustering coefficients will attract other nodes to form communities centered by them. Based on these results, the autonomous production control and management of smart shop floor will become more accurate, efficient, and balanced.

In order to realize the online allocation of collaborative processing resource of smart workshop in the context of cloud manufacturing, a multi-objective optimization model of workshop collaborative resources (MOM-WCR) was proposed. Considering the optimization objectives of processing time, processing cost, product qualification rate, and resource utilization, MOM-WCR was constructed. Based on the time sequence of workshop processing tasks, the workshop collaborative manufacturing resource was integrated in MOM-WCR. Fuzzy analytic hierarchy process (FAHP) was adopted to simplified the multi-objective problem into the single-objective problem. Then, the improved firefly algorithm which integrated the particle swarm algorithm (IFA-PSA) was used to solve MOM-WCR. Finally, a group of connecting rod processing experiments were used to verify the model proposed in this paper. The results show that the model is feasible in the application of workshop-level resource allocation in the context of cloud manufacturing, and the improved firefly algorithm shows good performance in solving the multi-objective resource allocation problem.

No abstract

Under the autonomous production mode, the production and operation process of smart shop-floor is operated by manufacturing units themselves. This paper describes a new framework for the order-driven products processing based on cloud-edge collaboration, in which the production-logistics tasks are planned and scheduled by the manufacturing resources at the bottom of smart shop-floor. The key enabled technologies and roadmap are further pointed out. The core idea of autonomous production mode is the autonomous communication and collaboration through an industrial network between all physical resources during production in a shop-floor. It is intended to serve as a reference for the managers while handling the flexible production organization and management based on the dynamic customer requirements.