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Research on Inventory Control of Nokia Siemens Network Sha Factory

Author: ZhaoLiZuo
Tutor: ChenZuo; ZhaoQingRong
School: Shanghai Jiaotong University
Course: Logistics Engineering
Keywords: inventory control multi-ABC classification order model demandforecast
CLC: F274
Type: Master's thesis
Year: 2012
Downloads: 101
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Abstract


The rapid development of communication technologies causes frequentmodification of customer requirements in terms of product upgrading and deliverydate. Currently, many communication equipment manufacturing enterprises are facingchallenges such as frequent modification of customer demand, short lead time ofcustomer order, and inventory control problem. Therefore, inventory control hasbecome an important issue of manufacturing enterprise management. In the leanproduction theory, the ultimate goal of inventory control is to reduce inventory andachieve "zero inventory" which is crucial for the manufacturing cost savings andincrease the economic benefit. This paper analyzes the current inventory control ofNSN SHA factory based on the project of NSN shanghai factory inventoryOptimization. It first studies the main products, materials’ supply and demand. Thenwe discuss the current inventory control situation of NSN SHA factory, focusing onthe issue of high inventory capital, low inventory turn rate and poor healthy inventoryratio. At last, it presents the methodology to improve NSN SHA factory inventorycontrol based on the advanced inventory control theory and the modern inventorymanagement methods.This paper first introduces the basic theory of inventory control and presentsseveral methods of the prediction of customer demand and inventory management.Then, it emphasizes the importance of demand prediction and inventory control. Withthese on hand, we further investigate the factory of NSN Shanghai to understand itssupply chain management and material inventory situation. Specifically, thecharacteristics of hybrid production lines of various products output, the nature ofmaterials and the order mode are then analyzed. Based on the investigation, wesuggest that it is helpful to reduce market uncertainty and forecasting error throughselecting appropriate forecasting methods. The results help enterprises to adopt correctinventory control policy and reduce inventory.Secondly, based on the ABC classification method, this paper proposes amulti-ABC classification method referencing the project priority, material supply riskfactors etc. to form a more reasonable material classification. The proposed classification method suggests different inventory control strategy and ordering modelfor different kinds of materials to ensure the balance of the three inventory costs(inventory gain cost, inventory holding cost, inventory shortage cost). Meanwhile, theintegrated management mode of MRP and JIT are needed along with the utilization ofKANBAN to improve production line material delivery process. It is also acompulsory for further research on study to satisfaction of customers’ demand on timeunder the premise of the lowest inventory cost.In addition, one constraint for inventory analysis strategy is demand forecast.Since the demand is from customers, the prospect of the market is non-controllable forthe corporate SCM staff. As a result, we should choose a suitable forecasting tool as amonitoring method. Only by seizing the market requirement faster, will it be possiblefor us to achieve satisfactory forecast result. So, inventory controlling shall, first of all,resolve problems right from the cause of the inventory, in other words, forecastproblems.Finally, we employ the real data to illustrate that by implementing the goodinventory control strategy, NSN SHA factory inventory status is largely improved.Moreover, the paper discusses the future research direction for further continuousimprovement of the inventory control.

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