Campus Units

Statistics

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

2018

Journal or Book Title

Journal of Quality Technology

Volume

50

Issue

2

First Page

135

Last Page

149

DOI

10.1080/00224065.2018.1438007

Abstract

Big data features not only large volumes of data but also data with complicated structures. Complexity imposes unique challenges on big data analytics. Meeker and Hong (2014; Quality Engineering, pp. 102–16) provided an extensive discussion of the opportunities and challenges on big data and reliability; they also described engineering systems which generate big data that can be used in reliability analysis. Meeker and Hong (2014) focused on large-scale system operating and environment data (i.e., high-frequency multivariate time series data) and provided examples on how to link such data as covariates to traditional reliability responses such as time to failure, time to recurrence of events, and degradation measurements. This article intends to extend that discussion by focusing on how to use data with complicated structures to do reliability analysis. Such data types include high-dimensional sensor data, functional curve data, and image streams. We first provide a review of recent developments in those directions, then we provide a discussion on how analytical methods can be developed to tackle the challenging aspects that arise from the complex features of big data in reliability applications. The use of modern statistical methods such as variable selection, functional data analysis, scalar-on-image regression, spatio-temporal data models, and machine-learning techniques will also be discussed.

Comments

This is an Accepted Manuscript of an article published by Taylor & Francis as Hong, Yili, Man Zhang, and William Q. Meeker. "Big data and reliability applications: The complexity dimension." Journal of Quality Technology 50, no. 2 (2018): 135-149. DOI: 10.1080/00224065.2018.1438007 . Posted with permission.

Copyright Owner

Taylor & Francis

Language

en

File Format

application/pdf

Published Version

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