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Forecasting warranty claims for recently launched products

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  • Wu, Shaomin
  • Akbarov, Artur

Abstract

Forecasting warranty claims for recently launched products that have short histories of claim records is vitally important for manufacturers in preparing their fiscal plans. Since the amount of historical claim data for such products is not large enough, developing forecasting models with good performance has been a difficult problem.

Suggested Citation

  • Wu, Shaomin & Akbarov, Artur, 2012. "Forecasting warranty claims for recently launched products," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 160-164.
    • Handle: RePEc:eee:reensy:v:106:y:2012:i:c:p:160-164
    DOI: 10.1016/j.ress.2012.06.008
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    References listed on IDEAS

    as
    1. Murthy, D. N. P. & Djamaludin, I., 2002. "New product warranty: A literature review," International Journal of Production Economics, Elsevier, vol. 79(3), pages 231-260, October.
    2. Wu, Shaomin & Akbarov, Artur, 2011. "Support vector regression for warranty claim forecasting," European Journal of Operational Research, Elsevier, vol. 213(1), pages 196-204, August.
    3. David Stephens & Martin Crowder, 2004. "Bayesian analysis of discrete time warranty data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 53(1), pages 195-217, January.
    4. Majeske, Karl D., 2007. "A non-homogeneous Poisson process predictive model for automobile warranty claims," Reliability Engineering and System Safety, Elsevier, vol. 92(2), pages 243-251.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Yang, Duo & He, Zhen & He, Shuguang, 2016. "Warranty claims forecasting based on a general imperfect repair model considering usage rate," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 147-154.
    2. Wu, Shaomin, 2013. "A review on coarse warranty data and analysis," Reliability Engineering and System Safety, Elsevier, vol. 114(C), pages 1-11.
    3. Wu, Shaomin, 2014. "Construction of asymmetric copulas and its application in two-dimensional reliability modelling," European Journal of Operational Research, Elsevier, vol. 238(2), pages 476-485.
    4. Zhou, Chongwen & Chinnam, Ratna Babu & Dalkiran, Evrim & Korostelev, Alexander, 2017. "Bayesian approach to hazard rate models for early detection of warranty and reliability problems using upstream supply chain information," International Journal of Production Economics, Elsevier, vol. 193(C), pages 316-331.
    5. Chehade, Abdallah & Savargaonkar, Mayuresh & Krivtsov, Vasiliy, 2022. "Conditional Gaussian mixture model for warranty claims forecasting," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    6. Gupta, Sanjib Kumar & Chattopadhyay, Gaurangadeb, 2022. "Early detection of reliability related problems from two-dimensional warranty data considering labour code priority index," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    7. Chehade, Abdallah & Hassanieh, Wael & Krivtsov, Vasiliy, 2024. "SeqOAE: Deep sequence-to-sequence orthogonal auto-encoder for time-series forecasting under variable population sizes," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    8. Shokouhyar, Sajjad & Ahmadi, Sadra & Ashrafzadeh, Mahdi, 2021. "Promoting a novel method for warranty claim prediction based on social network data," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    9. Gupta, Sanjib Kumar & De, Soumen & Chatterjee, Aditya, 2014. "Warranty forecasting from incomplete two-dimensional warranty data," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 1-13.

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