考量車輛保固期及回廠率之服務性零件存貨模型研究

近年來因成本占售價比例的上升、平均車齡的延長及購車考量因素等，各家車廠皆在利潤更高且規模日益擴大的售後服務有更多策略因應。而考量到服務廠的設備、時間、人力及其他因素的限制，提升回廠率是售後服務中最重要的議題之一。一般消費者在新車保固期內受限於保固條款的限制，大多仍會回原廠進行保修，除了活動營銷的誘因外，最基本的服務水準也會影響回廠意願，若在保固期內未滿足顧客零件需求，後續來訪的機會就可能因此受影響。因此本研究以保固期內車輛為研究對象，比較不同車款之回廠率差異並改良需求預估模型且配合個案公司現行定期盤存制架構，建構更精準的存貨管理模型，最後比較同在個案公司設定的目標服務水準下與現行做法的成本差異，並提出實務上管理的意涵，供個案公司在存貨管理策略上參考。分析結果顯示結合回廠率並以迴歸方程式做為需求預估的依據，更能掌握零件需求較不穩定的情況，而個案公司的移動平均法較適合用於需求波動較小的零件成熟期。分類基準是影響零件需求預估及存貨模型效率的因素之一，若以零件種類當作部分的參數設定，應用在特定零件會缺乏個體的異質性，造成偏誤的產生，而依照零件本身需求特性為分類標準，會使建立模型的結果更加精準。最後若要達到設定之目標服務水準，會增加零件庫存量，亦會造成其成本增加，但缺貨狀況會因此改善。但若為了減少成本而降低存貨，則會造成缺貨情況大幅提升，影響到服務水準及顧客滿意度。

關鍵字

服務性零件；保固期；回廠率；服務水準；需求預測；零件存貨管理

並列摘要

In recent year owing to the increasing percentage of cost to price ratio, the extension of average vehicle age and the consideration of car purchase, many car manufacturers have more strategies on aftersales that has higher profits and gradually expanding scale. Improving the return rate is one of the most important issue of aftersales considering limitations of the workshop equipment, time, manpower and other factors. Most of the consumers will still return to the dealers’ workshop within the warranty period limited by the warranty terms. In addition to the incentives of marketing, service level will also affect willingness to return to the dealers’ workshop. To meet the customer's parts needs, subsequent visits may be affected. If the parts demand aren’t satisfied within warranty period, then the willingness to return would be impacted. Therefore, this research takes the vehicle within warranty period as the research object, compares the difference in return rate of different models, revises the demand forecasting model, and combines it to the case company's current periodic inventory system to construct a more accurate inventory management model. At last, it compares the cost difference between the research result and the current practice at the case company's target service level and proposes practical management implications for the case company's reference in inventory management strategy. The analysis results show that the combination of the return rate and the regression equation are the basis for demand forecasting which can better grasp the fluctuated parts demand and moving average method of the case company that is more suitable for the mature period of parts with less fluctuation in demand. The standard of classification is one of the factors that affects the parts demand forecasting and the efficiency of the inventory model. If the part categories are used as parameter setting and applied to specific parts, the results would be biased due to lack of individual heterogeneity. But if by using parts demand as the classification criteria, the results of the model building would be more accurate. At last, if it has to achieve target service level, it will increase parts inventory and cost, but back order situation will be improved. However, if the inventory is reduced in order to reduce costs, the shortage will be greatly improved, affecting the service level and customer satisfaction.