Abstract
With the rapid development of the manufacturing industry and the advancement of the intelligent process, the scheduling problem of complex manufacturing systems becomes more and more complicated, especially in the aspect of energy management and optimization. This study aims to propose an online scheduling mathematical optimization strategy based on thermal energy optimization and fuzzy mathematical model, so as to improve the scheduling efficiency and resource allocation rationality of complex manufacturing systems under different production conditions. A scheduling model considering thermal energy utilization rate, production priority and real-time demand is established by using fuzzy mathematics. The model deals with the uncertain factors by fuzzy logic and solves them by genetic algorithm to realize the dynamic adjustment and optimal scheduling of production resources. Through the experimental verification of a complex manufacturing system, the improvement of scheduling efficiency not only reduces the operating cost, but also improves the flexibility and response speed of the system. The fuzzy mathematical model based on thermal energy optimization provides an effective on-line scheduling strategy for complex manufacturing systems, which can realize efficient scheduling and energy management in dynamic environment.
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