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论文编号：	16136
作者编号：	2320234042
上传时间：	2026/6/9 1:25:35
中文题目：	一汽丰田售后零件供需管理数智化改进研究
英文题目：	Research on the Digitized Improvement of Supply and Demand Management of After sales Parts for FAW Toyota
指导老师：	杨斌
中文关键字：	需求预测；零件供需管理；安全库存；数智化改进；及时供应率
英文关键字：	Demand Forecasting；Parts Supply and Demand Management；Safety Inventory；Digital Improvement；Timely Supply Rate
中文摘要：	车企主要销售整车与售后零件两类实物商品。随着市场竞争日趋白热化，汽车市场已从增量市场转向存量市场，整车业务增利难度不断加大。一汽丰田自2003年9月25日成立以来，累计销量已超1200万台，涉及零件的售后服务对公司盈利水平提升及品牌忠诚度维系至关重要。目前系统内注册的零件种类近25万种，规模庞大，其供需管理质量不仅影响零件销售目标的达成，更关系到公司经营合规性（零件需满足10年保供要求）。优质的售后零件供需管理需综合考量上游生产、市场及时供应率、自身库存水平及零件呆滞风险，在供应稳定性与成本控制之间实现平衡。然而当前，一汽丰田中国本土售后零件供应体制与海外其他市场存在差异，更为复杂，人工管理模式已难以适配，因此，研究一汽丰田中国本土售后零件供需管理，探索适配中国市场的优化策略，对公司持续改善经营、实现良性发展，以及保障千万车主享受优质售后服务具有重要意义。 本文首先分析了研究背景与意义，指出当前售后零件管理面临及时供应率低、库存风险高、断货频发等问题。通过文献回顾，梳理了市场需求预测、库存设定策略及供应链管理等相关理论。其次，深入剖析了一汽丰田售后零件供需管理现状，发现主要问题源于需求预测精度不足、产销协同不畅、库存结构不合理及人工管理精细化程度低。在此基础上，提出了数智化改进策略，运用AI大模型提升市场需求预测精度，优化订货、生产、交货流程，改进库存结构与安全库存设置。最后预估了数智化改进方案的实施效果，并提出组织结构改革、考核机制优化等技术保障措施。研究表明，数智化改进能有效提升售后零件供需管理效率，可以为汽车企业和其它制造业企业售后零件管理提供参考。
英文摘要：	Automobile enterprises mainly sell two types of physical products: whole vehicles and after-sales parts. With the increasingly fierce market competition, the automotive market has shifted from an incremental market to a stock market, and the difficulty of increasing profits from the whole vehicle business is constantly increasing. Since its establishment on September 25, 2003, FAW Toyota has achieved a cumulative sales volume of over 12 million vehicles, and after-sales services involving parts are crucial for improving the company's profitability and maintaining brand loyalty. At present, nearly 250,000 types of parts are registered in the system, with a huge scale. The quality of its supply and demand management not only affects the achievement of parts sales targets, but also is related to the company's operational compliance (parts need to meet the 10-year supply guarantee requirement). High-quality after-sales parts supply and demand management needs to comprehensively consider upstream production, market timely supply rate, own inventory level and parts obsolescence risk, and achieve a balance between supply stability and cost control. However, at present, the local after-sales parts supply system of FAW Toyota in China is different from that of other overseas markets and is more complex, making the manual management mode difficult to adapt. Therefore, studying the supply and demand management of FAW Toyota's local after-sales parts in China and exploring optimized strategies suitable for the Chinese market are of great significance for the company to continuously improve its operations, achieve sound development, and ensure that 10 million car owners enjoy high-quality after-sales services. This paper first analyzes the research background and significance, pointing out that the current after-sales parts management is facing problems such as low timely supply rate, high inventory risk and frequent stockouts. Through literature review, it sorts out relevant theories such as market demand forecasting, inventory setting strategy and supply chain management. Secondly, it deeply analyzes the current situation of FAW Toyota's after-sales parts supply and demand management, and finds that the main problems stem from insufficient demand forecasting accuracy, poor coordination between production and sales, unreasonable inventory structure and low refinement of manual management. On this basis, it proposes digital and intelligent improvement strategies, using AI large models to improve the accuracy of market demand forecasting, optimize the ordering, production and delivery processes, and improve the inventory structure and safety stock settings. Finally, it estimates the implementation effect of the digital and intelligent improvement plan, and puts forward technical guarantee measures such as organizational structure reform and assessment mechanism optimization. The research shows that digital and intelligent improvement can effectively improve the efficiency of after-sales parts supply and demand management, and can provide a reference for after-sales parts management of automobile enterprises and other manufacturing enterprises.
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