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特钢行业备件库存管理的研究与应用
引用本文:刘晓冰,邱立鹏,王万雷.特钢行业备件库存管理的研究与应用[J].计算机集成制造系统,2007,13(9):1756-1761.
作者姓名:刘晓冰  邱立鹏  王万雷
作者单位:1. 大连理工大学,CIMS中心,辽宁,大连,116024
2. 大连民族学院,机械系,辽宁,大连,116600
摘    要:在保障生产运行的情况下,为达到合理占有库存资金的目的,提出了一种基于备件库存相关特性分类的备件库存管理方法.该方法将备件的库存方式进行分类,根据分类结果定义备件的分类树,将缺货成本、库存成本、采购成本、零件使用频率、备件供应情况和备件需求预测作为分类节点问题,使用模糊神经网络,确定其中需要多属性判断节点的值,最终依据备件分类树和库存策略表,实现对备件的分类库存管理.最后,给出了某特钢集团企业资源计划系统中该模块的软件实现.

关 键 词:备件库存  备件分类  库存策略  模糊神经网络  特钢行业  备件需求预测  库存管理  研究  应用  enterprise  steel  special  软件实现  模块  企业资源计划系统  集团  策略表  判断  多属性  神经网络  模糊  使用频率  问题  节点
文章编号:1006-5911(2007)09-1756-06
收稿时间:2006-11-01
修稿时间:2007-03-12

Spare parts inventory management in special steel enterprise
LIU Xiao-bing,QIU Li-peng,WANG Wan-lei.Spare parts inventory management in special steel enterprise[J].Computer Integrated Manufacturing Systems,2007,13(9):1756-1761.
Authors:LIU Xiao-bing  QIU Li-peng  WANG Wan-lei
Abstract:To keep the factory running smoothly with reasonable spare parts inventory fund, a new spare parts inventory management method was proposed based on the property classification of spare part inventory.Firstly,the spare part inventory styles were classified.Then,a decision tree was defined based on classification result with shortage cost,inventory cost,purchase cost,spare part utilization frequency,spare part supply condition and spare part requirement forecast as the nodes of the tree.The value of the node was decided by fuzzy neural network if multi-attribute decision was needed.Finally,the classification management of spare parts inventory strategy was realized by using the decision tree and inventory strategy table.Software implementation of the model in a special steel enterprise's ERP system was also presented.
Keywords:spare parts inventory  spare parts classification  inventory strategy  fuzzy neural network
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