Optimization Study On Semi-finished Garment Label Inventory Plan Of Aili Guangzhou Company

Along with the rapid growth of economy,enterprises embrace constant development and business scale expansion,which is accompanied with more and more challenges as well.In this complex operation environment,supply chain plays a pivotal role to link front-product development to end-shop floor execution,plus back-end suppliers management.All problems occurred among the whole process leads to unreasonable inventory rise and cost increasing,which stops enterprises from fast growing.And during the process,a good inventory management is the key element for enterprises to reduce cost,uplift benefits and finally achieve great growth.As a great foreign-funded enterprise,Allie specializes in retail branding and intelligent solutions specialized in garment label.However,due to the lack of scientific inventory management theories,and experimentalism on demand and supply planning,Allie meets a series of challenges,including high cost,large capital occupation and inappropriate inventory structure.Under the theoretical guidance of supply chain management,inventory planning,and demand planning,this thesis firstly builds up demand model by collecting and analyzing order data;and secondly predict demand trend by utilizing Exponential Smoothing(ES in short),and then matches demand with inventory planning with support of scientific product taxonomy;and finally create an optimized inventory plan and guarantee the best execution after simulating the plan.This thesis aims to create a scientific method for semi-finished inventory management.What makes retail branding labels special is its regular seasonally changing demand model.With Allie’s demand data in three years,this thesis analyzes the seasonal demand model by category,and verify the seasonal similarity of different years by Multi-dimensional vector cosine value,to finalize the seasonal demand model;and then predict the seasonal demand by Exponential Smooth to support inventory planning to the most.This research will greatly contribute to Allie on cost saving,efficiency improvement and benefit growth,also can function as a guidance for similar products’ demand and inventory planning.