随着科技的不断进步，个人消费类电子产品以及智能终端设备快速普及和小型化，由于 此类电子产品的生产制造离不开高精度自动化组装设备，从而 加工企业对高精度自动化设备 的需求持续上升；当前电子产品表面贴装（SMT）的高精度自动化设备依然依赖于进口，而 自动化设备的售后零配件支持服务的时效性，是影响自动 化设备制造企业与其终端客户电子 加工制造企业的有序经营、持续发展的重要保障因素。 本论文通过分析U企业与其终端客户之间的自动化设备零配件供给存在问题，对多个终 端客户的配件库存实际状况进行研究分析，发现U企业在同一区域的多个终端客户均有各自 的紧急配件库存，但各终端客户的零配件库存信息相互独立，客户端配件缺货问题时有 发生， 为了减少配件造成设备的宕机时间，常需要设备供应商，在终端客户之间进行配件的协调借 调工作来缩短配件的响应时间。本文从U企业的终端客户实际需求出发，减少因 配件问题引 起的设备宕机时间进行研究分析。 论文首先介绍研究背景和意义；其次介绍自动化设备零配件管理的相关理论和方法；接 着分析U企业零配件供应链的构成和运营模 式，运用ABC分类法对G系列设备的配件进行 分类，提出基于G系列设备下的零配件优化方案，以及基于配件分类的零配件库存优化方案， 基于该优化方案对U企业的N区域三家终端 客户的零配件库存进行协同优化柔性调配。收集 分析客户端设备宕机时间的构成，发现设备故障的排查判定所耗费的时间占设备总宕机时间 约41%，基于此状况，提出设备分类下 的配件使用、故障判定排查、预防的优化方案：如何 提高配件的使用寿命、提高设备故障排查判定效率；针对配件不同故障原因提出相应的预防 改善措施；根据不同配件的故障 频率和特征，运用不同的定量分析和预测方法进行优化改善， 如运用Spass工具软件对控制类Cont11配件进行定量分析预测；同时运用Minitab工具软件 对Cont11进行仿真验证， 仿真结果和实际需求误差小于10%；对于一些设计寿命较长（>5 年）的配件，根据浴盆曲线理论，运用平均故障事件MTBF方法进行预测此类配件的需求量。 通过集聚客户端配 件库存信息进行优化协调，客户端设备宕机得到明显的改善，从8.7%降到 4.6%，异常配件故障下降70%；N区域客户端G系列设备配件无库存比率下降为17%，同时 U企业可以详细了 解终端客户的配件库存量和使用状况，为上海仓库的配件库存量调整提供 了有效的数据支持，并有效的降低U企业自身配件的库存量和成本，降低配件缺货风险。 关键词:零配件 分类,自动化设备,零配件库存管理，需求预测 II Abstract With the continuous progress of science and technology, personal consumer electronic products and intelligent terminal equipment are rapidly popularized and miniaturized. As the production manufacturing of such electronic products cannot be done without high-precision automatic assembly equipment, the SMT processing enterprises' demand for high-precision automatic equipment continues to rise. At present, high-precision automation equipment of SMT is still dependent on import, and the timeliness of after-sales spare parts support service of automation equipment is an important guarantee factor affecting the orderly operation and sustainable development of automation equipment vendor and their terminal customers' electronic processing and manufacturing enterprises. In this paper by analyzing the relation between the U enterprise and its terminal customers, the spare parts supply problems, accessories inventory to multiple end users through analyzing the actual situation, found that U company has multiple end users have thir own emergency accessories inventory in same area, but the spare parts inventory information are independent, and the end users’ parts shortage problem occurred frequently. To reduce machine downtime that cause by the parts shortage issue, the U company need coordinate the end customers to accessories secondment work to shorten the parts response time. Based on the actual needs of the end customers of U company, this paper conducts research and analysis to reduce the equipments’ downtime that caused by parts’ problem. Firstly, the research background and significance are introduced. Secondly, it introduces the related theories and methods of automation equipment spare parts management. Then analysis U enterprise spare parts supply chain structure and operation mode, using the ABC classification to classify G series equipment spare parts, based on G series equipment of spare parts optimization scheme, as well as the spare parts inventory optimization scheme based on parts classification, based on the optimization scheme for U company’ s three end customer spare parts inventory for the collaborative optimization of flexible deployment in N area. Collect and breakdown the end users’ equipment downtime, found the troubleshooting time greater than 41% of the total downtime, base on it,puts forward equipment classification, issue troubleshooting, prevention, the optimization of the scheme, how to improve the life time of parts, improve the efficiency of equipment troubleshooting; Put forward corresponding preventive and improvement measures according to different fault causes. According to the fault frequency and characteristics of different parts, different quantitative analysis III and prediction methods are used for optimization and improvement. For example, Spass tool software is used for quantitative analysis and prediction of Cont11 control parts. At the same time, Minitab tool was used to simulate and verify Cont11, and the error between the simulation result and the actual demand was less than 10%. For some parts with a long life (>5 years), according to the bathtub curve theory, and the MTBF method is used to predict the demand of such parts. By gathering the inventory information of the end customers’ parts for optimization and coordination, the downtime of the client equipment was significantly improved, from 8.7% to 4.6%, and the malfunction of abnormal parts decreased by 70%. N regional customer' G series equipment accessories without inventory ratio is reduced to 17%, at the same time U enterprises can got detail information about spare parts inventory and use condition of end customer, these data can support Shanghai warehouse do parts inventory adjustment, and effectively reduce the U their own parts inventory and cost, reduce the risk of parts out of stock. Key words: Parts Classification; Automation Equipment; Spare Parts Inventory Management; Demand Forecasting IV 目录 第一章 绪论 ............................................................................................................................................................. 1 研究背景与意义 ........................................................................................................................................ 1 1.1.1 研究背景 ......................................................................................................................................... 1 1.1.2 研究意义 ......................................................................................................................................... 1 文 献综述 .................................................................................................................................................... 2 1.2.1 国外研究现状 ................................................................................................................................. 2 1.2.2 国内研究现状 ................................................................................................................................. 2 研究思路与研 究内容 ................................................................................................................................ 4 第二章 自动化设备配 件管理相关模式 ................................................................................................................. 5 零配件分类相关方法 ................................................................................................................................ 5 零配件需求预测相关方法 ........................................................................................................................ 6 零配件库存管理相关模式 ............................................................................