Moving towards Real-time Data-driven Quality Monitoring: A Case Study of Hard Disk Drives

被引：16

作者：

Mashhadi, Ardeshir Raihanian ^{[1
]}

Cade, Willie ^{[2
]}

Behdad, Sara ^{[1
,3
]}

机构：

[1] Univ Buffalo, Mech & Aerosp Engn Dept, Buffalo, NY 14260 USA

[2] ICR Management, Chicago, IL 60651 USA

[3] Univ Buffalo, Dept Ind & Syst Engn, Buffalo, NY 14260 USA

来源：

46TH SME NORTH AMERICAN MANUFACTURING RESEARCH CONFERENCE, NAMRC 46 | 2018年 / 26卷

基金：

美国国家科学基金会;

关键词：

Cloud manufacturing; data-driven quality and health monitoring; predictive maintenance; hard disk drive failure prediction;

D O I：

10.1016/j.promfg.2018.07.147

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Since its emergence, the cloud manufacturing concept has been transforming the manufacturing and remanufacturing industry into a big data and service-oriented environment. The aggressive push toward data collection in cloud-based and cyber-physical systems provides both challenges and opportunities for predictive analytics. One of the key applications of predictive analytics in such domains is predictive quality management that aims to fully exploit the potentials provided by the enormous data collected via cloud-based systems. As a case study, a data set of hard disk drives' Self-Monitoring, Analysis and Reporting Technology (SMART) attributes from a cloud-storage service provider has been analyzed to derive some insights about the challenges and opportunities of using product lifecycle data. An analysis of time-to-failure monitoring of hard disk drives in real-time has been carried out and the corresponding challenges have been discussed. (C) 2018 The Authors. Published by Elsevier B.V.

引用

页码：1107 / 1115

页数：9

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