Research On Optimization Of Collaborative Manufacturing Chain For Task With Time-Sequence Constraint

With the development of network technology and manufacturing technology, networked manufacturing is widely researched and applied. It is now becoming a new paradigm for manufacturing industry. Under the networked manufacturing environments, the utilization and optimization deployment of networked manufacturing resources for manufacturing task is the key and basic technology for realizing the constructing of Collaborative Manufacturing Chain (CMC), and has been a new study hotpot in the integration manufacturing field. This paper is oriented to the practical requirements of complicated components subcontract machining and cooperative manufacturing among medium-small manufacturing enterprises in the east of Zhejiang province. It is deeply researched that mathematical modeling of the constructing process for CMC, programming of the structure for manufacturing task, optimization modeling for CMC and application of the system.The research results are summarized as:(1) The process characteristics of the constructing of CMC are deeply researched, and it is pointed that the constructing process is the bidirectional optimization process between manufacturing tasks and manufacturing resources. The new conceptions, including Collaborative Manufacturing Chain (CMC), Task with Time-Sequence Constraint (TTSC) and Collaborative Manufacturing Unit (CMU) and so on, are advanced. The model of TTSC and the process mathematical model of CMC are proposed. By analyzing the standard and non-standard solution set of TTSC, the corresponding standard and non-standard solution set of constructing schemes for CMC are educed. Then the market forms of the standard and horizontal CMC are given.(2) For the structure optimization of collaborative manufacturing task, the span model of TTSC is proposed. By analyzing the key factors from decomposing schemes, collaborative cost and production period of manufacturing task under the networked manufacturing environments, the mathematical models between TTSC and above-mentioned influential factors is developed. The optimization design for TTSC is quasi-quantitatively analyzed, and the optimal span value is obtained. Based on the programming for TTSC, a decomposing scheme of manufacturing task is set up for core manufacturing resources. Then the techniques for decomposing and aggregating manufacturing task are analyzed.(3) The problems of constructing optimization model for CMC are studied. After analyzing the characters in constructing process of optimization of tasks performances parameters and deployment of resources, the models of Euclidean Distance of performances parameters of manufacturing tasks vectors are proposed based on the double-direction optimization framework. Then the mathematical optimization models for performances parameters of manufacturing tasks of CMC are developed. For the character of horizontal CMC, fully applying the surplus manufacturing competencies of collaborative CMU, the multi-objective optimization model is set up based on the optimization criteria of comprehensive cost minimization and production load among CMU balancing. For the optimization problem of the standard CMC, the linked cost between CMU, penalty cost from tardiness and the surplus manufacturing competencies of collaborative CMU are considered, then the multi-objective optimization model is developed based on the optimization criteria of comprehensive cost minimization and production load among CMU minimization.(4) The solution algorithms and simulation for optimization model are studied. For the optimization of performances parameters of manufacturing tasks of CMC, the function characteristics are analyzed. The adaptive genetic algorithm is used to solve the function, and the schemes of real coding and adaptive changing genetic operators are designed and model transformation for the target function is implemented. Because the optimization models for standard and horizontal CMC are multi-objective, the non-dominated sorting genetic algorithm II is applied to solve the functions based on the conceptions of Pareto optimal. The simulation studies are implemented for the above models and algorithms, and the effectiveness of models are validated.(5) The system construction and operation flow of CMC Optimization Supported System (CMCOSS) are designed and a prototype system is developed. Taking the cooperative manufacturing of auto bear axle as typical cases, the running results of CMCOSS are given. Thus, the theory and method proposed in this dissertation are validated.