Big Data-Driven Manufacturing—Process-Monitoring-for-Quality Philosophy

Author:

Abell Jeffrey A.1,Chakraborty Debejyo2,Escobar Carlos A.2,Im Kee H.2,Wegner Diana M.2,Wincek Michael A.2

Affiliation:

1. GM Technical Fellow Mem. ASME Global Research and Development, General Motors, Warren, MI 38092 e-mail:

2. Global Research and Development, General Motors, Warren, MI 38092 e-mail:

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

ASME International

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Control and Systems Engineering

Reference38 articles.

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