Michael Anthony Wincek

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

Discussion of big data 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 has 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 that is founded on big data and big model, which are catalysts for the next step in the evolution of the quality movement. Process monitoring for quality was used to evaluate the performance of the ultrasonically welded battery tabs in the new Chevrolet Volt, an extended range electric vehicle. Index terms — Manufacturing, big data, big models, problem solving strategy, process monitoring for quality, acsensorization, quality control Nomenclature α rate of type I error β rate of type II error BD big data BDBM big data – big models BM big models D3M data-drive discovery of models DFSS design for six sigma DLL dynamic-link library GP genetic programming ICE internal combustion engine LVDT linear variable differential transformer MCS multiple classifier systems MPCD maximum probability of correct decision PMQ process monitoring for quality