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The Research Of Logistics Layout And Storage Strategies In Sand Core Coveying Line

Posted on:2017-03-22Degree:MasterType:Thesis
Country:ChinaCandidate:C WangFull Text:PDF
GTID:2309330488993363Subject:Mechanical and electrical engineering
Abstract/Summary:PDF Full Text Request
The main function of sand core coveying line is to transport sand core from making center to modeling center. Automation sand core coveying line can be adapted to the harsh environment of high temperature as well as avoiding dangerous of manual operation. It can also improve the efficiency of sand core transportation. The research makes it more convenient to in and out of warehouse as well as reducing the costs of warehouse management.The research focus on two themes include logistics distribution planning and storage strategies.The article researched layout planning of sand core conveying line based on the from-to chart which is drown according to conveying line’s technology roadmap.Find out the optimal path of all from-to chart by programming in order to layout the conveying line.The article researched the blockage reason of the conveying line under the different working mode according to the analysis of equipment unit and logistics transportation network-Proposed a control strategy of confluence node to determine the interval between conveying units.The article proposed basic strategy of storing sand core to stereoscopic warehouse. The reason of stereoscopic warehouse’s low efficiency is find out and it’s efficiency can be improved by readjust the position of goods in stereoscopic warehouse when stacking machine are vacant. Genetic algorithms have been applied in order to improve the efficiency of stacking machine. Genetic have been designed according to structure of stacking machine’s path. For similar, cross operator, variation operator and select operator have been designed according to genetic’s features. It’s easy to establish genetic algorithm model to find out optimal path. Using C# language to programming PC control software to calculate the optimal path and verified algorithm model’s effectiveness.
Keywords/Search Tags:Layout Planning, Confluence Node, Path Optimization, Genetic Algorithm
PDF Full Text Request
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