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Research On Data Driven Inventory Management And Control Technology In Parts Value Chain

Posted on:2020-03-07Degree:MasterType:Thesis
Country:ChinaCandidate:H Y WangFull Text:PDF
GTID:2392330590496417Subject:Software engineering
Abstract/Summary:PDF Full Text Request
Sales and ownership of automobiles in China are increasing in recent years.Profits by after-sales service are also increasing.Perfect after-sales service can help automobile enterprises establish a good brand effect.The main profit of after-sales service comes from automobile parts sales.Automobile companies want to provide good after-sales service to customers,it is very important to control parts inventory.From the point of view of TJ automobile manufacturer,this paper studies the technology of parts inventory management and control,and proposes the method of establishing parts demand forecasting model and purchasing plan guidance through BP neural network to control parts inventory.The implementation is to forecast the quantity of parts demand and make purchasing plan guidance based on this quantity.At the same time,the automobile industry value chain collaborative cloud platform has many automobile manufacturers,and accumulated a large number of related parts procurement,sales,production and other data.Based on Echarts,this paper visualized the historical parts business data of TJ automobile manufacturer in various dimensions and constructed parts inventory management and control archives.In the platform,TJ is only one of the automobile manufacturing enterprises.Because of the characteristics of information resources sharing,the platform provides data for the research of inventory control technology of parts across the value chain.The paper explores the inventory control technology of parts across the chain.Based on the text similarity algorithm BM25 in natural language processing,the algorithm will select ten match parts in different enterprise value chains for the same part.The research uses C # as programming language,based on the three-tier architecture of B/S mode to complete the development.According to requirements,three modules are realized,which are the inventory management and control archives of parts,the demand forecasting management of parts and the cooperative exploration of parts across the chain.This paper describes the relevant process of design and development,as well as the development environment and main function implementation steps.If the operator of TJ automobile factory matches the same part correctly,he can inquire about the inventory of parts of YC in WP transfer repository,which provides effective information for the subsequent cross-chain allocation of parts.However,this paper does not realize the cross-chain allocation of parts.
Keywords/Search Tags:Parts Requirement Prediction, BP Neural Network, BM25
PDF Full Text Request
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