Big Data-Driven Manufacturing—Process-Monitoring-for-Quality PhilosophySource: Journal of Manufacturing Science and Engineering:;2017:;volume( 139 ):;issue: 010::page 101009Author:Abell, Jeffrey A.
,
Chakraborty, Debejyo
,
Escobar, Carlos A.
,
Im, Kee H.
,
Wegner, Diana M.
,
Wincek, Michael A.
DOI: 10.1115/1.4036833Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Discussion of big data (BD) has been about data, software, and methods with an emphasis on retail and personalization of services and products. Big data also has impacted engineering and manufacturing and has resulted in better and more efficient manufacturing operations, improved quality, and more personalized products. A less apparent effect is that big data have changed problem solving: the problems we choose to solve, the strategy we seek, and the tools we employ. This paper illustrates this point by showing how the big data style of thinking enabled the development of a new quality assurance philosophy called process monitoring for quality (PMQ). PMQ is a blend of process monitoring and quality control (QC) that is founded on big data and big model (BDBM), which are catalysts for the next step in the evolution of the quality movement. Process monitoring (PM) for quality was used to evaluate the performance of the ultrasonically welded battery tabs in the new Chevrolet Volt, an extended range electric vehicle.
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contributor author | Abell, Jeffrey A. | |
contributor author | Chakraborty, Debejyo | |
contributor author | Escobar, Carlos A. | |
contributor author | Im, Kee H. | |
contributor author | Wegner, Diana M. | |
contributor author | Wincek, Michael A. | |
date accessioned | 2017-11-25T07:17:56Z | |
date available | 2017-11-25T07:17:56Z | |
date copyright | 2017/24/8 | |
date issued | 2017 | |
identifier issn | 1087-1357 | |
identifier other | manu_139_10_101009.pdf | |
identifier uri | http://138.201.223.254:8080/yetl1/handle/yetl/4234850 | |
description abstract | Discussion of big data (BD) has been about data, software, and methods with an emphasis on retail and personalization of services and products. Big data also has impacted engineering and manufacturing and has resulted in better and more efficient manufacturing operations, improved quality, and more personalized products. A less apparent effect is that big data have changed problem solving: the problems we choose to solve, the strategy we seek, and the tools we employ. This paper illustrates this point by showing how the big data style of thinking enabled the development of a new quality assurance philosophy called process monitoring for quality (PMQ). PMQ is a blend of process monitoring and quality control (QC) that is founded on big data and big model (BDBM), which are catalysts for the next step in the evolution of the quality movement. Process monitoring (PM) for quality was used to evaluate the performance of the ultrasonically welded battery tabs in the new Chevrolet Volt, an extended range electric vehicle. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Big Data-Driven Manufacturing—Process-Monitoring-for-Quality Philosophy | |
type | Journal Paper | |
journal volume | 139 | |
journal issue | 10 | |
journal title | Journal of Manufacturing Science and Engineering | |
identifier doi | 10.1115/1.4036833 | |
journal fristpage | 101009 | |
journal lastpage | 101009-12 | |
tree | Journal of Manufacturing Science and Engineering:;2017:;volume( 139 ):;issue: 010 | |
contenttype | Fulltext |