Warranty forecasting from incomplete two-dimensional warranty data

Warranty modelling with incomplete data is a major issue in reliability analysis. The incomplete failure region characterized by warranty field data may be classified into several domains representing failures from manufacturing/assembly defects, usage or fatigue. In the present paper a data driven...

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Veröffentlicht in:Reliability engineering & system safety 2014-06, Vol.126, p.1-13
Hauptverfasser: Gupta, Sanjib Kumar, De, Soumen, Chatterjee, Aditya
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Sprache:eng
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Zusammenfassung:Warranty modelling with incomplete data is a major issue in reliability analysis. The incomplete failure region characterized by warranty field data may be classified into several domains representing failures from manufacturing/assembly defects, usage or fatigue. In the present paper a data driven approach has been suggested to demark the regions optimally through estimation of the change point in a hazard function. In the perspective of bivariate warranty analysis, as relevant in automobiles, we have assumed the lifetime distribution to be a mixture of distributions corresponding to the burn-in period and the useful life period. The proportions of observations in different regions demarketed by the warranty policy in the bivariate plane have been estimated by considering mileage along with age. The estimation scheme has been verified and validated through extensive simulation studies. The utilities of the results have been demonstrated by addressing several issues through a real life synthetic warranty data set from a large automobile company. •Detailed responses to all comments of the reviewers are attached in a separate file. Almost all of the suggestions of the reviewers are incorporated in the revised manuscript.•Some recent works of different authors as mentioned by the reviewers have been included in the revised manuscript.•The term change point with reference to the transition from $DFR$ to $CFR$ part of the bath-tub curve has been elaborated.•A sample of real life data has been given in the revised manuscript in Table $4$, by following the suggestion of reviewer 2.•The findings have been summarised in a better way in the conclusion part. In this portion we have emphasized on the take away of our work. Scopes for future work have also been mentioned.
ISSN:0951-8320
1879-0836
DOI:10.1016/j.ress.2014.01.006