P公司鼠标器产品零部件库存管理研究

发布时间：2018-05-26 05:02

本文选题：需求不确定性 + 需求分析与预测　；参考：《华南理工大学》2013年硕士论文

【摘要】：信息技术的高速发展，已引领我们进入经济全球化的时代，而经济全球化加剧了产业竞争。另一方面,美国次贷危机和欧债危机的影响造成了整个世界经济下滑,且需求的减少进一步加剧了同业之间的竞争。企业要在这场竞争中占有一席之地，必须能够适时、适量地给客户提供有价格竞争力的产品及服务。为达成以上目标，许多企业都致力于技术创新、提高自动化程度以提升生产力，同时努力降低材料采购成本及控制库存成本。因应需求的不确定性，要适时、适量地提供客户所需产品及服务，企业除了提升自己的生产力之外，也必须能够对需求做出科学的分析和预测并采用科学的库存控制方法。库存控制是企业管理的核心工作之一。本文以P公司鼠标器产品零部件库存管理问题为研究对象，结合P公司鼠标器产品零部件库存管理过程中所面临的实际问题，运用需求预测及库存控制相关理论和方法，提出适合P公司鼠标器零部件库存管理的方法，解决企业库存管理实际问题。本文首先列举了国内外学者针对零部件库存控制研究的现状，相比较而言，国外学者，特别是日本及美国在这方面的研究比较早，而且也较成熟。近年来，由于物流成本的不断上升，库存控制已成为影响国内企业经营绩效的重要因素之一。因此，国内也开始涌现出众多学者，投身于企业库存控制问题方面的研究。但总体来说，国内学者对电脑周边行业同时应用以下方法进行零部件库存控制展开研究者尚不多见：应用时间系列做零部件需求预测、应用ABC分类法对零部件做分类管理且应用供应商管理库存模式（VMI）做库存管理。其次,通过对P公司鼠标器厂的实地调研，了解其需求预测及零部件库存控制的现状：零部件需求预测数据完全依赖于客户提供的成品需求预测，通过成品BOM结构展开及跑MRP获得；订购数量比较随机且订购方法单一；供应链各节点企业在库存信息交流方面的互动很少，库存水平高居不下。笔者通过对现状进行分析，了解到P公司在零部件库存管理方面存在以下问题：需求预测准确率低、零部件缺乏分类管理且采购策略单一、缺乏与供应商在供应链协作方面的密切配合。再者，针对需求预测准确率低之问题，通过对P公司的需求形态进行分析，笔者发现其需求呈现平稳时间序列分布特点。通过应用简单移动平均法对2012年的需求进行预测，准确率达92.92%。最后，针对零部件缺乏分类管理且采购策略单一及缺乏与供应商在供应链协作方面的密切配合等问题，笔者应用ABC分类法对P公司鼠标器零部件进行分类，，并给出算例说明如何应用定量订购法及定期订购法分别对AB及C类零部件实施库存管理，并进一步提出应用供应商管理库存法对A类及部分B类零部件进行库存控制。希望该研究能为其他企业的零部件库存控制提供参考。
[Abstract]:The rapid development of information technology has led us into the era of economic globalization, and economic globalization has intensified industrial competition. On the other hand, the impact of the subprime mortgage crisis in the United States and the European debt crisis caused the whole world economy to decline, and the reduction of demand further intensified the competition among the peers. In order to have a place in this competition, enterprises must be able to provide their customers with competitive products and services in a timely and appropriate manner. To achieve these goals, many enterprises are committed to technological innovation, increased automation to improve productivity, while efforts to reduce material procurement costs and control inventory costs. In response to the uncertainty of demand, enterprises must be able to make scientific analysis and prediction of demand and adopt scientific inventory control methods in order to provide the products and services required by customers in a timely and appropriate manner, in addition to improving their own productivity. Inventory control is one of the core tasks of enterprise management. This paper takes the stock management of the mouse parts of P Company as the research object, combining with the actual problems in the process of the stock management of the mouse parts of P company, using the theories and methods of demand forecasting and inventory control. This paper puts forward a method for stock management of mouse parts in P Company to solve the practical problems of inventory management in enterprises. This paper first lists the domestic and foreign scholars on the research status of parts inventory control, compared with the foreign scholars, especially Japan and the United States in this area of research is early, but also more mature. In recent years, due to the rising logistics costs, inventory control has become one of the important factors affecting the performance of domestic enterprises. Therefore, there are many scholars in our country who devote themselves to the research of enterprise inventory control. But generally speaking, domestic scholars on the computer peripheral industries at the same time using the following methods to carry out inventory control researchers have not seen: the use of time series to predict the demand for parts, The ABC classification method is used to classify the parts and the VMI model is used to manage the inventory. Secondly, through the field investigation of the mouse factory of P Company, we can find out the current situation of demand forecasting and parts inventory control: the forecasting data of parts demand totally depend on the demand forecast of finished products provided by customers. The order quantity is random and the ordering method is single. The exchange of inventory information between the enterprises in each node of the supply chain is very little and the inventory level is high. By analyzing the present situation, the author finds out that P company has the following problems in the management of spare parts inventory: the accuracy of demand prediction is low, the parts lack of classified management, and the purchasing strategy is single. Lack of close coordination with suppliers in supply chain collaboration. Furthermore, aiming at the problem of low accuracy of demand forecasting, the author finds that the demand of P company presents the characteristics of stable time series distribution through the analysis of the demand pattern of P Company. By using the simple moving average method to forecast the demand in 2012, the accuracy is 92.92%. Finally, aiming at the problems of lack of classification management, single purchasing strategy and lack of close cooperation with suppliers in supply chain cooperation, the author applies ABC classification method to classify the mouse parts of P Company. An example is given to illustrate how to use the quantitative ordering method and the periodic ordering method to carry out inventory management for AB and C parts respectively. Furthermore, the application of Vendor Management inventory method to the inventory control of Class A and part B parts is put forward. It is hoped that this study can provide reference for other enterprises in the control of spare parts inventory.
【学位授予单位】：华南理工大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F274;F426.6

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