Industrial data analytics for diagnosis and prognosis : a random effects modelling approach

"Today, we are facing a data rich world that is changing faster than ever before. The ubiquitous availability of data provides great opportunities for industrial enterprises to improve their process quality and productivity. Industrial data analytics is the process of collecting, exploring, and...

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Bibliographic Details
Main Authors Zhou, Shiyu, 1970- (Author), Chen, Yong (Professor of industrial and systems engineering) (Author)
Format Electronic eBook
LanguageEnglish
Published Hoboken, New Jersey : John Wiley & Sons, Inc., [2021]
Subjects
Industrial engineering > Statistical methods.
Industrial management > Mathematics.
Random data (Statistics)
Estimation theory.
elektronické knihy
electronic books
Online AccessFull text
ISBN9781119666271
1119666279
9781119666295
1119666295
1119666309
9781119666301
9781119666288
Physical Description1 online resource : illustrations (some color)

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Table of Contents:
  • Introduction to data visualization and characterization
  • Random vectors and the multivariate normal distribution
  • Explaining covariance structure : principal components
  • Linear model for numerical and categorical response variables
  • Linear mixed effects model
  • Diagnosis of variation source using PCA
  • Diagnosis of variation sources through random effects estimation
  • Analysis of system diagnosability
  • Prognosis through mixed effects models for longitudinal data
  • Prognosis using Gaussian process model
  • Prognosis through mixed effects models for time-to-event data.

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