Classification Models of Spare Parts Based on Demand Characteristics
Ren Xi
BI Peng
ZHANG Xiaofei
Abstract：Spare parts classification is the basis for spare parts demand forecasting research.Only on the basis of correct spare parts classification, the research on spare parts demand forecasting can be carried out better.Mainly starting from not commonly used spare parts features the needs of the average demand data, time and extent of changes in demand interval demand for spare parts are rough classified.On the basis of rough classification, average demand interval and coefficient of variation of the two parameters of non-zero values are extracted for classification model needs quantitative analysis, these needs not only to consider the needs of property intermittent and massive resistance, but also consider the unexpected requirements.The sudden demand for property space to expand into account sudden demand will greatly increase demand classification accuracy.The classification method is applied by the classification attribute mapping variables to predict the best method, the best prediction method for a given sequence is obtained by mapping needs.
Keywords：rarely used spare partsdemand characteristicsclassificationmassive demand
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 74-76,92 )