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Research On Material Classification And Inventory Control Strategy Of C Company

Posted on:2023-05-05Degree:MasterType:Thesis
Country:ChinaCandidate:H Q LiFull Text:PDF
GTID:2558306845993049Subject:Industrial Engineering and Management
Abstract/Summary:PDF Full Text Request
In the process of enterprise operation,inventory plays an important role,among which material management is an important part.Good material inventory management can not only adjust the imbalance between supply and production,but also help enterprises face the fierce competitive environment,alleviate the pressure brought by the rapidly changing market,and realize the stable operation of enterprises.C Company is the epitome of many small and medium-sized enterprises in the field of medical device production,and has the typical characteristics of such enterprises-light inventory,heavy production and extensive management.It usually uses high inventory to meet customer needs and avoid stock out.However,ignoring inventory is easy to hide problems in the process of enterprise management.High inventory reserves are easy to affect the capital turnover,easy to form a backlog,and make the competitive advantage of enterprises not obvious.With the expansion of enterprise production,how to reduce inventory costs and improve customer satisfaction and market share without affecting enterprise services is a problem to be considered and solved by C company.This paper mainly studies and analyzes the specific operation of C company,summarizes its production mode,analyzes its inventory management status and existing problems,and puts forward solutions to the classified management of materials and the optimization of inventory control.The specific research is as follows:(1)Solve the problem of extensive material classification of the company,comprehensively consider the classification indicators of materials,classify the materials based on multiple indicators of fuzzy clustering,improve the traditional ABC classification method,summarize the results by using the core principles of ABC classification,and realize the fine classification of materials of C company.(2)In the cluster analysis of materials,the multi index system of materials is constructed;Select four quantitative indicators and two qualitative indicators from the economic characteristics,use characteristics,supply and important characteristics of materials,and interview enterprise experts to quantify the qualitative indicators;Then the index is processed by entropy weight.Finally,the refined material classification under fuzzy c-means clustering is completed by MATLAB,and compared with the traditional ABC classification results.(3)To solve the problem of material inventory control based on experience,the company uses the key factor affecting material ordering-demand fluctuation to distinguish the stability of material demand,and develops solutions to different inventory control strategies for different types of materials.The ideal material with stable demand adopts(q,Q)management strategy;For the key materials with non-stationary demand,the static and dynamic inventory control strategy is adopted,and this strategy is emphatically described.Under the condition of meeting the relevant service level constraints,the multi cycle modeling solution of such materials is carried out to achieve the minimum sum of the ordering cost and inventory holding cost,so as to realize the dynamic management of such materials.(T,S)management strategy is adopted for general materials with stable demand.The traditional management strategy is still used for the materials with special customization needs,and inventory management suggestions are provided for the stagnant materials.Finally,the effect and sensitivity of different strategy models are established,verified and compared.At the same time,it puts forward relevant improvement suggestions for other aspects of inventory management of C company.There are 23 spokes in figure,23 tables and 53 references.
Keywords/Search Tags:Medical device, Inventory material classification, Inventory control optimization, SMEs
PDF Full Text Request
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