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Aggregate discounted warranty cost forecasting considering the failed-but-not-reported events

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  • Wang, Xin
  • Xie, Wei
  • Ye, Zhi-Sheng
  • Tang, Loon-Ching

Abstract

Warranty claims usually incur substantial costs to the manufacturers. In practice, it is not accurate or economical to reserve money for future claims based on the prediction of the overall (life cycle) warranty cost. As a more appropriate alternative, the aggregate warranty cost forecast technique can reduce the liquidity risks and improve the warranty service efficiency. In addition, when a product fails during the warranty period, a warranty claim will be counted only when the customer reports the failure to the manufacturer. This paper focuses on forecasting the discounted warranty cost, which depends on the product sales and failure processes, warranty terms, and customer behaviors, over arbitrary time interval. To characterize the failed-but-not-reported phenomenon, a flexible time-dependent function is proposed. We derive the mathematical formulations of related factors to discuss the modeling process of total discounted warranty cost over an arbitrary time interval (TDWCATI). The impacts of warranty length and customer reporting behavior are explored. The expectation and variance of the TDWCATI are obtained under the pro-rata warranty policy and the nonrenewable minimal-repair policy, which shows that the TDWCATI is useful in planning future warranty services and budgets over a specific time period.

Suggested Citation

  • Wang, Xin & Xie, Wei & Ye, Zhi-Sheng & Tang, Loon-Ching, 2017. "Aggregate discounted warranty cost forecasting considering the failed-but-not-reported events," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 355-364.
    • Handle: RePEc:eee:reensy:v:168:y:2017:i:c:p:355-364
    DOI: 10.1016/j.ress.2017.04.009
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    References listed on IDEAS

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    2. Liu, Xintian & Mao, Kui & Wang, Xiaolan & Wang, Xu & Wang, Yansong, 2020. "A modified quality loss model of service life prediction for products via wear regularity," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    3. Shang, Lijun & Liu, Baoliang & Qiu, Qingan & Yang, Li, 2023. "Three-dimensional warranty and post-warranty maintenance of products with monitored mission cycles," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    4. Lijun Shang & Guojun Shang & Qingan Qiu, 2022. "A Bivariate Post-Warranty Maintenance Model for the Product under a 2D Warranty," Mathematics, MDPI, vol. 10(12), pages 1-18, June.
    5. Lijun Shang & Xiguang Yu & Liying Wang & Yongjun Du, 2022. "Design of Random Warranty and Maintenance Policy: From a Perspective of the Life Cycle," Mathematics, MDPI, vol. 10(20), pages 1-22, October.
    6. Chehade, Abdallah & Savargaonkar, Mayuresh & Krivtsov, Vasiliy, 2022. "Conditional Gaussian mixture model for warranty claims forecasting," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    7. Lijun Shang & Xiguang Yu & Yongjun Du & Anquan Zou & Qingan Qiu, 2022. "An Optimal Random Hybrid Maintenance Policy of Systems under a Warranty with Rebate and Charge," Mathematics, MDPI, vol. 10(18), pages 1-19, September.
    8. Cao, Zixia, 2022. "Brand equity, warranty costs, and firm value," International Journal of Research in Marketing, Elsevier, vol. 39(4), pages 1166-1185.
    9. Wang, Yukun & Liu, Yiliu & Li, Xiaopeng & Chen, Junyan, 2019. "Multi-phase reliability growth test planning for repairable products sold with a two-dimensional warranty," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 315-326.
    10. Wei Xie, 2017. "Optimal pricing and two-dimensional warranty policies for a new product," International Journal of Production Research, Taylor & Francis Journals, vol. 55(22), pages 6857-6870, November.
    11. Wu, Shaomin & Do, Phuc, 2017. "Editorial," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 1-3.

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