配电网备品备件库存定额研究

发布时间：2018-03-08 14:48

本文选题：配电网备品备件　切入点：支持向量机　出处：《华南理工大学》2014年硕士论文　论文类型：学位论文

【摘要】：鉴于电网企业的专业性与特殊性，配电网备品备件在满足设备检修维护需要的同时，还需尽量减少库存积压和占用库存资金，以保障电网生产的安全性与经济性，实现电网企业的高效运营。因此，合理的库存需求预测模型、科学的库存管理策略以及库存定额算法对提高备品备件管理水平是非常必要的。在此背景下，本文以G供电局为研究对象，对配电网备品备件的需求预测、管理策略及库存定额展开具体研究。本文首先通过实践调研等方式收集G供电局配电网备品备件库存管理现状的相关信息，梳理资料并进行详细的现状问题分析。总结出G供电局配电网备品备件现行的库存管理中存在的物资采购计划具有盲目性、物资分类不合理、物资出入库记录存在纰漏、库存定额不科学和库存管理模式过于传统等问题。通过研究库存需求预测的相关理论以及配电网备品备件的特征，本文基于支持向量机回归预测法（SVM，，Support Vector Machine）提出适用于配电网备品备件的需求预测模型。模型有效考虑了物资的历史需求量、检修计划、设备故障率以及运行环境这四个影响物资需求的因素，最后以抢修物资柱上断路器为例验证需求预测方法的合理性与可行性。本文还提出了适用于配电网备品备件的AB分类库存管理策略以及库存定额算法。首先将G供电局配电网备品备件划分成A、B（包括B1和B2）两大类，研究确定其相应的库存控制管理模型，并以物资需求预测结果为基础，为A、B类物资分别建立各自库存管理模型下的库存定额算法，最后以算例补充说明库存定额管理算法的实际应用。此外，本文针对G供电局还引入虚拟库存管理策略，为解决实物库存管理存在的缺陷提出了虚拟库存具体应用建议。算例结果表明，本文所提的库存需求预测模型，配电网备品备件的分类管理方法、库存管理控制策略以及库存定额算法能有效改善G供电局现行库存管理中存在的问题，对配电网备品备件库存管理具有良好的工程应用价值。
[Abstract]:In view of the specialty and particularity of power grid enterprises, the spare parts of distribution network should not only meet the needs of maintenance and repair of equipment, but also reduce the backlog of inventory and occupy stock funds as far as possible, so as to ensure the safety and economy of power grid production. Therefore, reasonable inventory demand forecasting model, scientific inventory management strategy and inventory quota algorithm are very necessary to improve spare parts management level. Taking G power supply bureau as the research object, this paper studies the demand forecast, management strategy and inventory quota of spare parts in distribution network. Firstly, this paper collects relevant information about the status of spare parts inventory management in distribution network of G Power supply Bureau by means of practical investigation and research. Combing the data and analyzing the current situation in detail, summing up the material purchase plan existing in the current inventory management of spare parts in the distribution network of G Power supply Bureau is blind, the material classification is unreasonable, the material entry and storage record is flawed, The stock quota is not scientific and the inventory management mode is too traditional. By studying the theory of inventory demand forecasting and the characteristics of spare parts in distribution network, Based on the support vector machine regression prediction method, this paper presents a demand forecasting model for spare parts in distribution network. The model effectively considers the historical demand of materials and maintenance plan. The failure rate of equipment and the operating environment are the four factors that affect the material demand. Finally, the rationality and feasibility of the demand prediction method are verified by an example of the circuit breaker on the material post for emergency repair. This paper also puts forward the AB classification inventory management strategy and inventory quota algorithm suitable for distribution network spare parts. Firstly, the spare parts of G power supply bureau are divided into two categories: Agna B (including B1 and B2). This paper studies and determines the corresponding inventory control management model, and based on the forecast results of material demand, establishes the inventory quota algorithm for Agna B material under their respective inventory management model. Finally, an example is given to illustrate the practical application of the inventory quota management algorithm. In addition, this paper introduces virtual inventory management strategy for G power supply bureau, and puts forward some specific suggestions for the application of virtual inventory in order to solve the defects of physical inventory management. The results show that the forecasting model of inventory demand, the classified management method of spare parts in distribution network, the control strategy of inventory management and the algorithm of inventory quota can effectively improve the problems existing in the current inventory management of G Power supply Bureau. It has good engineering application value for spare parts inventory management in distribution network.
【学位授予单位】：华南理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM73

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