Aggregate Scheduling Of Machining And Heat Treatment In Complex Manufacturing Systems

With the rapid development of science and technology, the products become more and more advanced and complicated, which results in great challenges in production for those manufacturing enterprises. Enterprises not only need to focus on the machining processes of parts, but also need to pay more attention to the heat treatment processes, and the assembly relationship between them. How to schedule the parts in such a complex manufacturing system, in order to ensure deliveries, reduce inventory costs, keep the production cycle balance, and improve the utilization of heat treatment furnaces, has become a challenging issue in both research and industry communities.This thesis analyzes the related researches, and then considering the real production environment, an in-depth study is presented on the machining and heat treatment integrated scheduling problem. The features of machining operations and heat treatment operations, as well as the machining machines and heat treatment furnaces are analyzed. The similarities and differences between them are extracted. The production resources constraints are also analyzed. Based on these, an integrated scheduling problem of machining and heat treatment model is proposed, and the scheduling objective functions are given.In response to the model, a solution framework is designed. In this framework the machining operations scheduling and the heat treatment operations scheduling can be integrated together. First, the heat treatment operations of parts are analyzed, and heat treatment batches division mechanism are built. Then schedule the machining operations of the parts, during which, heat treatment batches are scheduled. In this manner the scheduling of machining operations and heat treatment operations are integrated together.This thesis also designs a multi-agent negotiation mechanism based on the scheduling algorithm for machining operations. The related objects are modeled using multi-agents. Agents negotiate with each other through a market mechanism which is similar to bargaining to determine the optimal solution.Finally, simulation experiments are designed to evaluate the performances of the proposed algorithm by comparing with other solutions. Simulation results verify the feasibility and effectiveness of the proposed algorithm in this thesis.