Under industry 4.0, the production control system of smart job shop should be able to real-time respond to various production events and effectively coordinate different kinds of manufacturing resources in good order according to their material flows. Production events enabled real-time production control system is good at responsibility and flexibility. Internet of things (IoT) can provide enormous real-time production events, which represent the change of material flows. However, some of production events seriously interfere with production control procedures. They sharply restrict the real-time capability of production control system. Thus, it is imperative that an efficient realization method of production control system, which is enabled by useful production events. Additionally, the control system should satisfy production control procedures visibility. For solving the problems, a production events graphical deduction model enabled real-time production control system for smart job shop is proposed in this article. Firstly, the manufacturing resources are divided into work in process related, operator-related, cutting tool-related, fixture tool-related, and measuring tool-related. And the material flows of different manufacturing resources in IoT-enabled smart job shop are described in detail. Secondly, the graphical deduction model of production event is put forward. Based on the model, the material flows of manufacturing resources in a process are segmented into several stages according to different production events. And then, the cooperation model of manufacturing resources is established by using the time and logical relationships between production events. Thirdly, the control model in a process is drawn from the cooperation model. Next, the entire control procedure of work in process production in IoT-enabled smart job shop is proposed. Finally, a small-scale IoT-enabled manufacturing system is used to verify the feasibility of the proposed model and methods.
Application of Machine Learning and Rule Scheduling in a Job-Shop Production Control System