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    政大機構典藏 > 商學院 > 資訊管理學系 > 期刊論文 >  Item 140.119/120870
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/120870


    Title: A Dynamic Failure Rate Forecasting Model for Service Parts Inventory
    Authors: Chen, Ta-Yu
    Lin, Woo-Tsong
    林我聰
    Sheu, Chwen
    Contributors: 資管系
    Keywords: green supply chains;reverse logistics;third-party repair service providers;failure rate forecast;service parts;bathtub curve theory;Markov Decision Process
    Date: 2018-07
    Issue Date: 2018-11-09 15:07:18 (UTC+8)
    Abstract: This study investigates one of the reverse logistics issues, after-sale repair service for in-warranty products. After-sale repair service is critical to customer service and customer satisfaction. Nonetheless, the uncertainty in the number of defective products returned makes forecasting and inventory planning of service parts difficult, which leads to a backlog of returned defectives or an increase in inventory costs. Based on Bathtub Curve (BTC) theory and Markov Decision Process (MDP), this study develops a dynamic product failure rate forecasting (PFRF) model to enable third-party repair service providers to effectively predict the demand for service parts and, thus, mitigate risk impacts of over- or under-stocking of service parts. A simulation experiment, based on the data collected from a 3C (computer, communication, and consumer electronics) firm, and a sensitivity analysis are conducted to validate the proposed model. The proposed model outperforms other approaches from previous studies. Considering the number of new products launched every year, the model could yield significant inventory cost savings. Managerial and research implications of our findings are presented, with suggestions for future research.
    Relation: SUSTAINABILITY, 10(7), 2408
    Data Type: article
    DOI 連結: http://dx.doi.org/10.3390/su10072408
    DOI: 10.3390/su10072408
    Appears in Collections:[資訊管理學系] 期刊論文

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