Demand Predicting And Management Optimization Of Metro Operational Materials In City A

The operating scale of Metro in city A is expanding,which has become an important mode of transportation for urban residents.The operational materials are essential for supporting and ensuring the normal and safe operation of metro.How to classify the tens of thousands of items and reasonably forecast goods demand to improve inventory management and reduce the inventory cost is a question worth thinking and researching.This paper takes Metro of city A as the research object.First of all,it analyzes the present situation of logistics management,showing the unreasonable method of inventory control,irrational inventory structure,high inventory costs and low inventory turnover rate.So it is necessary to find a suitable method to solve the above problems.Then this paper classifiesthe 11608 items of metro operational materials in cityAbased on the ABC-FSN classification method.By constantly trying and exploring all kinds of prediction model,the regression model is used to forecast the demand of production parts in material AF,the ARIMA model is used to forecast the demand of production material CF,CS and AF,and the ARIMA model is used to forecast the demand of material BF.The relevant data indicates that the above three forecasting models can be used for metro operational materials.Finally,it optimizes all kinds of materials purchasing process and warehouse management,and achieves the purpose of reducing the overall cost and improving procurement efficiency.