Abstract
The purpose of this paper is to assist in measuring all costs associated with product warranties including the environmental problems and in estimating the potential warranty cost savings. The concept of the green warranty is emphasized in this paper because of its effect on increasing the scope of warranty cost savings. This paper suggests a new concept for the design of warranty system that combines some of neural network approaches in green IT’s point of view. In particular, Gompertz function is used as the transfer functions in the model. The academic importance of this study is that Gompertz can be a type of mathematical model for green warranty claims, where warranty growth is slowest at the start and end of warranty lifetime period. To apply the model to warranty data, the practitioners need not identify parametric distributions for the failure attributes. To demonstrate the model, this paper develops a neural network mixture model for the automotive warranty data.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
We’re sorry, something doesn't seem to be working properly.
Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.
References
Yadav NS, Chinnam RB, Goel PS (2003) A fuzzy logic based approach to reliability improvement estimation during product development. Reliab Eng Syst Saf 80:63–74
Lolas S, Olatunbosun OA, Steward D, Buckingham J (2007) Fuzzy logic knowledge base construction for a reliability improvement expert system. In: Proceedings of the world congress on engineering, 2007
Ferrari S, Stengel RF (2005) Smooth function approximation using neural networks. IEEE Trans Neural Netw 16(1)
Liao SH (2003) Knowledge management technologies and applications—literature review from 1995 to 2002. Expert Syst Appl 25:155–164
Rai B, Singh N (2003) Hazard rate estimation from incomplete and unclean warranty data. Reliab Eng Syst Saf 81:79–92
Kim HG, Rao BM (2000) Expected warranty cost of two-attribute free-replacement warranties based on a bivariate exponential distribution. Comput Ind Eng 38:425–434
Lawless JF (1998) Methods for the estimation of failure distributions and rates from automobile warranty data. Lifetime Data Anal 1:227–40
Majeske KD (2003) A mixture model for automobile warranty data. Reliab Eng Syst Safety 81:71–77
Lee S-H, Lee S-J, Moon K-I, Kim B-K (2008) Decision of abnormal quality unit lists from claim database. J Inf Process Syst 4(3)
Lee S-H, Cho S-E, Moon K-I (2010) Fast fuzzy control of warranty claims system. J Inf Process Syst 6(2)
Lee S-H, Cho S-E, Moon K-I (2010) Neural network approach for greenery warranty systems. In: The 6th international conference on intelligent computing, ICIC 2010 Changsha, China, 18–21 Aug 2010
Lee S-H, Lee S-J, Moon K-I (2010) A fuzzy logic-based approach to two-dimensional automobile warranty system. J Circuits Syst Comput 19(1):139–154
Lee S-H, Lee S-J, Moon K-I (2011) A two-attribute green warranty model for automobile warranty data. In: International conference on computer convergence technology, Seoul Korea, 20–22 Oct 2001, pp 444–449
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Science+Business Media Dordrecht
About this paper
Cite this paper
Lee, SH., Lee, SJ., Moon, KI. (2013). A Neural Network Mixture Model for Green Warranty Diffusion. In: Kim, K., Chung, KY. (eds) IT Convergence and Security 2012. Lecture Notes in Electrical Engineering, vol 215. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5860-5_127
Download citation
DOI: https://doi.org/10.1007/978-94-007-5860-5_127
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-5859-9
Online ISBN: 978-94-007-5860-5
eBook Packages: EngineeringEngineering (R0)