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Automotive sheet metal processing intelligent scheduling system design

Author: ZhouYueE
Tutor: SunYaMin;LiDongBo
School: Nanjing University of Technology and Engineering
Course: Pattern Recognition and Intelligent Systems
Keywords: Production of intelligent scheduling Spatial expression Split genetic algorithm
CLC: U468
Type: Master's thesis
Year: 2010
Downloads: 57
Quote: 0
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With the development of the modern market economy , the needs of individual users more and more , faster and faster to market changes , business competition is increasingly fierce . The original manual production process control is increasingly unable to meet the market development of modern manufacturing enterprises . Modern manufacturing companies need to be based on the specific circumstances of existing resources and a variety of constraints , for the needs of individual users to develop efficient production plan in order to improve production efficiency . A comprehensive analysis of the reality of the process of the production and processing of an auto parts company , enterprises manual control manually the production scheduling plan , there is a waste of resources , production plan cash is low and long production cycle and other issues . Existing production schedule has been unable to meet the changing market development is not conducive to long-term development of the enterprise , and the urgent need to improve . For the schedule many problems of the enterprises in the actual production process , detailed research and systems analysis , intelligent scheduling system solutions and implementations . First, the background of the subject , the reason , the status quo is a general description and analysis of the research status quo at home and abroad for the production of intelligent scheduling . Secondly , sheet metal shop smart car parts processing enterprises walkthrough drive system the whole idea , module design and process described and two physical models : composed by task pipes . Flux model and process - based three-dimensional space model; selected intelligent optimization algorithm genetic algorithm , and encoded in accordance with the traditional genetic algorithm , initialization , genetic operators design and fitness function design method , design the application process of the genetic algorithm , genetic operators will the crossover operator to change for the exchange operator , mutation operator Change operators for splitting and merging operator , thereby expanding the feasible solution space . Finally, the concrete realization of intelligent scheduling module design and development. Intelligent scheduling system solutions through the production of this study , it is possible to effectively reduce the intensity of production management jobs , improve production efficiency : real time control of the production process , reduce the cost of production and processing , which generates greater economic benefits for manufacturing companies .

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CLC: > Transportation > Road transport > Automotive Engineering > Automobile factory
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