Dynamic Scheduling Framework of the Flexible Mixed-Model Assembly Line Based on the Internet of Manufacturing Things

In mass customization (MC), the assembly operations of modular products tend to be organized as form flexible mixed-model line (FMMAL). The dynamic scheduling problem FMMAL is quite complex with product sequencing, station allocation, material delivery, disruption events failure, inserting and reworking. To solve these problems, a comprehensive framework combining architecture Internet Manufacturing Things (IoMT) algorithms proposed. Firstly, IoMT-based are constructed via multi-agent system (MAS) ubiquitous environment. Secondly, mathematical model formulated decision variables, optimization objectives constraint conditions. Thirdly, IoMT-oriented for proposed including fuzzy analytic hierarchy process (FAHP) normalization, weighted sum properties-improved genetic algorithm (WSP-IGA) prescheduling, priority weights search-simulated annealing (PWS-SA) rescheduling. Lastly, discrete event simulation numerical case conducted demonstrate practicality validity theories algorithms. results show that hyper-heuristics (WSP-IGA PWS-SA) can respectively realize prescheduling rescheduling in four modes synthesized mode, time-efficient just-in-time mode energy-saving which superior referenced meta-heuristics.