Cyber-physical manufacturing systems enabled by IoT and machine intelligence

Abstract

Abstract. CPMS have become a major facilitator of smart factories through a combination of physical operations and the computational intelligence and real-time communication. Combination of Internet of Things (IoT) technologies and machine intelligence offers novel possibilities to realize adaptive, efficient and autonomous manufacturing processes. Nevertheless, the co-ordination of the physical and cyber layer is a serious issue because of the dynamic characteristic of industrial set ups and the high amount of heterogeneous sensor data. This paper proposes a cyber-physical architecture based on the IoT, which uses machine intelligence to monitor, analyze, and control manufacturing systems in real-time. The approach that is proposed is based on sensor-driven data acquisition, intelligent processing, and adaptive decision-making to optimize system performance. To reduce the production inefficiency, energy usage as well as fault occurrence, a multi-objective formulation is created in the context of keeping operational constraints. The structure is tested on a realistic manufacturing case based on real-time data input. Findings indicate the improvement of operational efficiency, the capability of fault detection and the response time is reduced, compared to the traditional methods. The methodology suggested can be both scaled and powerful to serve next-generation intelligent manufacturing systems.