Lifetime prediction of vehicle components using online monitoring data

Chiharu Kumazaki, Watalu Yamamoto, Kazuyuki Suzuki

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)


In order to set an adequate lifetime target for each market, quantitative evaluation of variation of lifetime characteristics is required. In particular, the lifetime of vehicle unit depends heavily on customer's usage (e.g., gross vehicle weight, road gradient, and acceleration operation). We thus have developed an online monitoring system that continually collects some information such as usage and environmental conditions. A method has been developed for predicting vehicle component lifetimes using data from an online monitoring system that collects an extensive amount of data during vehicle operation. The linear model used for prediction takes into account variations in usage conditions and models' data as covariates. The prediction procedure was generalized to enable it to make predictions using a new data sample. The large amount of information on usage and environmental conditions obtained with the online monitoring system enabled the usage of each sample to be quantified and treated as a stratification factor. A stratified analysis produced fairly accurate results, meaning that using online monitoring data should be useful for lifetime prediction.

Original languageEnglish
Title of host publicationTheory and Practice of Quality and Reliability Engineering in Asia Industry
PublisherSpringer Singapore
Number of pages17
ISBN (Electronic)9789811032905
ISBN (Print)9789811032882
Publication statusPublished - 2017 Jan 1
Externally publishedYes


  • Cluster analysis
  • Cumulative damage model
  • Linear regression model
  • Principal component analysis
  • S-N curve

ASJC Scopus subject areas

  • Engineering(all)
  • Economics, Econometrics and Finance(all)
  • Business, Management and Accounting(all)


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