D公司备件需求预测研究
Research on the Demand Forecast of D Company's Spare Parts
Abstract
Spare parts are actually a kind of inventory, the main role of which is to ensure the
normal and effective operation of production equipment. Under normal circumstances, an
excessive stock of spare parts will, in a sense, occupy too much working capital, making the
company's operating costs increase significantly; insufficient stock of spare parts may lead to
a passive situation where no spare parts can be replaced, and may lead to serious production
accidents, such as work stoppages and production shutdowns. Therefore, the purpose of
effective spare parts management is to keep the spare parts inventory as low as possible while
maintaining the normal and effective operation of the equipment.
In this dissertation, based on the current situation of spare parts management in
Company D, through statistical analysis of spare parts management data in the process of
enterprise operation and maintenance, many problems of current spare parts management in
the company are explored, such as poor level of spare parts classification management and
low accuracy of spare parts consumption prediction. Subsequently, we analyzed the
characteristics of spare parts by using the indicators of demand volatility, trend and
periodicity as the benchmark, and classified them into four spare parts modules according to
continuous and discrete demands. Based on the four spare parts classification models and
their continuous and discrete characteristics, the paper constructs time series and gray forecast
spare parts demand forecasting models respectively, and selects five spare parts for model
fitting test to verify the validity and operability of the models. Finally, based on the demand
prediction and model validation results, this paper proposes countermeasures and safeguards
for the improvement of spare parts demand prediction management in Company D, such as
improving the spare parts outbound management process at a deeper level, strengthening
outbound inspection, and standardizing the management of warehouse and used spare parts, in
order to maximize the application value of enterprise spare parts demand management.
The results show that the method used in this dissertation is better than the original
demand forecasting method of company D. For example, the forecasting based on the
forecaster's experience can largely reduce the human errors caused by the lack of forecaster's
experience, and improve the accuracy and operability of the forecasting, and the sorting of
spare parts in Company D will be more scientific and feasible, and the safety stock quota will
be significantly reduced. Moreover, the adjusted and optimized spare parts demand control
mode and control mechanism will largely suppress the new low of spare parts inventory, and
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大连理工大学专业学位硕士学位论文
the company's spare parts inventory will show signs of decline and realize a virtuous cycle,
which will suppress the cost of spare parts management in Company D at a deeper level and
largely improve the economic efficiency of the company.
Key Words: Operation management; Demand forecast; Classification of spare parts;
Time series
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D公司备件需求预测研究
目录
摘 要.............................................................................................................................I
Abstract ..............................................................................................................................II
1 绪论.............................................................................................................................. 1
1.1 研究背景........................................................................................................... 1
1.2 研究目的及意义............................................................................................... 2
1.3 研究内容、研究方法及研究路线................................................................... 3
1.3.1 研究内容................................................................................................ 3
1.3.2 研究方法................................................................................................ 3
1.3.3 研究路线................................................................................................ 4
2 相关理论概述.............................................................................................................. 5
2.1 备件管理的概念与内容................................................................................... 5
2.1.1 备件管理的概念.................................................................................... 5
2.1.2 备件管理的内容.................................................................................... 6
2.2 备件管理理论与方法....................................................................................... 7
2.2.1 备件分类方法........................................................................................ 7
2.2.2 备件需求预测理论.............................................................................. 10
3 D公司备件需求预测管理现状及其存在问题分析................................................ 17
3.1 D公司的基本概况......................................................................................... 17
3.2 D公司备件管理及需求预测现状................................................................. 17
3.2.1 D公司备件信息管理系统现状.......................................................... 17
3.2.2 D公司备件需求预测现状.................................................................. 18
3.2.3 D公司备件库存量现状...................................................................... 19
3.3 D公司备件需求预测管理中存在问题......................................................... 21
3.3.1 D公司备件管理系统中备件库存分类不合理.................................. 21
3.3.2 备件需求预测模型准确率低.............................................................. 22
3.3.3 备件库存台账数据异常率高.............................................................. 22
3.4 D公司备件需求预测管理存在问题成因分析............................................. 22
3.4.1 需求预测中备件分类算法存在缺陷.................................................. 23
3.4.2 备件需求预测模型不得当.................................................................. 23
3.4.3 备件数据管理缺少相关的保障制度标准.......................................... 23
3.5 本章小结......................................................................................................... 23
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