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Multi Rules Production Scheduling Simulation Optimization in Discrete Manufacturing System

Author: LiuJingBo
Tutor: ChenXiaoHui
School: Chongqing University
Course: Industrial Engineering
Keywords: Discrete manufacturing systems Simulation and optimization Tabu Search Algorithm Rule-based scheduling
CLC: F273
Type: Master's thesis
Year: 2011
Downloads: 110
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Abstract


The production schedule is the core of modern production management , especially in discrete manufacturing systems , discrete manufacturing system scheduler is particularly difficult due to the randomness of the order , the dynamic nature of the production system and disproportion . Rules scheduling as production scheduling , easy to solve scheduling problems , more prominent scheduling scheme visibility and legibility for manufacturing core competitiveness of enterprises to enhance the economic efficiency of enterprises upgrade, enhance customer satisfaction , has a very important significance . Literature studies have shown that compared to the multi - rule scheduling a single rule scheduling can better improve the performance of production systems . Discrete manufacturing systems production scheduling of multi-rule approach is a combination of multiple rules introduce the idea of ??rule scheduling , considering the production systems of feeding, processing , handling , maintenance and other activities of a production scheduling method . This paper focuses on multi - rule scheduling method in discrete production system and solving the following research . ① discrete manufacturing system is divided into multiple decision points , including the processing activities and auxiliary processing activities , the introduction of scheduling rules and system parameters at each decision point , the average production cycle as the performance index , a combination of rules and system parameters as decision variables , build the production scheduling mathematical models for the discrete manufacturing system based on multi- rules , and proposed simulation and optimization methods for solving such problems . ( 2 ) based on the arena software integration and customization features , flexible simulation modeling method , the discrete manufacturing system simulation model is divided into functional modules , control and optimization modules , to build discrete manufacturing system simulation model and design control module scheduling rule base. ( 3 ) Select the tabu search as the optimization algorithm, tabu search algorithm for multi- rule scheduling and design , from the combination of tabu search algorithm and simulation model simulation model running events . ( 4 ) hot - cold drawn steel pipe production line , for example , analyze the system performance indicators of change in the simulation the number of repetitions , and select the appropriate number of repetitions as a simulation to optimize the conditions, optimizing results demonstrate the feasibility of this study .

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CLC: > Economic > Economic planning and management > Enterprise economy > Production management
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