Research of integrated cutting-stock system for intelligent manufacturing
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| Pubblicato in: | PQDT - Global (2008) |
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ProQuest Dissertations & Theses
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| Abstract: | Translation from original language as provided by authorThe cutting-stock problem has been concerned for a long period. Confronting the resource crisis, environment problem and serious pressure of commercial competition in new century, the demand for research of cutting-stock problem of manufacturing has developed from single packing optimization to integrated and intelligent optimization of the whole cutting-stock process. Combining with the present state and perspectives of manufacturing, the following research results has been acquired in this dissertation: (1) An integrated cutting-stock system for intelligent manufacturing is proposed. According to the problem that most attention has been paid on particular packing problem and complicated composite packing problem in manufacturing has been ignored, it's announced that the research of cutting-stock problem should be related with manufacturing anywhere. It's declared that the intelligent manufacturing system is themost comprehensive advanced manufacturing system after analyzing the present state and perspectives of manufacturing system and the concept, frameworks and key issues of the integrated cutting-stock system for intelligent manufacturing are introduced by concluding the characteristic of cutting-stock problem in manufacturing. (2) An Evaluation system of cutting-stock scheme based on analytic hierarchy Process (AHP) is established. According to the problem that cutting-stock scheme for intelligent manufacturing has related to many factors, the hierarchy of cutting-stock problem for intelligent manufacturing is established based on AHP, and fuzzy comprehensive evaluation system for cutting-stock scheme by the hierarchy is constituted. (3) Several intelligent packing algorithms are designed or improved, and integrated solution of packing algorithms for complicated composite packing problem is proposed. Referring to previous research results, T-Type algorithm for mass same-type polygons packing problem is proposed, hybrid genetic algorithm based on simulated annealing is structured and corresponding genetic coding methods, fitness evaluation function, arithmetic operators for packing problem are designed. Then multi-start-point, multi-path searching decoding algorithm for irregular polygons is designed based on analysis of classical bottom-left decoding algorithm for rectangles, decoding algorithm for polygons in multi-stock packing problem and decoding algorithm for promoting packing efficiency based on adaptive steps is proposed further more. Generally, the integration solution for complicated composite packing problem in manufacturing is proposed by handling the aforementioned intelligent algorithms on the condition of the demand of manufacturing. At last, the parallel genetic algorithm models are compared and a parallel packing algorithm framework is discussed. (4) A remnant characteristic extracting algorithm based on graph theory for cutting-stock problem is proposed. By translating the packing solution into digraph, the remnant characteristic extracting problem is translated into the problem of internal surfaces of digraph. After simplifying the digraph, a chain search algorithm based on depth first traversal is proposed to solve the problem. (5) Cutting path planning algorithms for non edge-shared packing problem and edge-shared packing problem are researched. The non edge-shared packing problem is structured as a generalized traveling salesman problem (GTSP) and translated into traveling sales man problem (TSP) by random keys coding method. The fitness function and genetic arithmetic operators of using genetic algorithm to solving the TSP is proposed. To edge-shared packing problem, the research result of Liu HuiXia of Jiangsu University is referred to translate it into the Euler circuit problem of undirected graph to solve it. (6) An integrated cutting-stock system for intelligent manufacturing is constructed. The flow and structure of the system is described based on the aforementioned research and corresponding module are designed. At last, the platform and key technologies in the process of developing the system are introduced and the application samples are |
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| Fonte: | ProQuest Dissertations & Theses Global |