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Approaches to Implement Statistical Process Control for Manufacturing in Big Data Era

[+] Author Affiliations
Shing I. Chang

Kansas State University, Manhattan, KS

Paper No. MSEC2017-2840, pp. V003T04A009; 7 pages
  • ASME 2017 12th International Manufacturing Science and Engineering Conference collocated with the JSME/ASME 2017 6th International Conference on Materials and Processing
  • Volume 3: Manufacturing Equipment and Systems
  • Los Angeles, California, USA, June 4–8, 2017
  • Conference Sponsors: Manufacturing Engineering Division
  • ISBN: 978-0-7918-5074-9
  • Copyright © 2017 by ASME


It has been long overdue to revamp existing statistical process control (SPC) approaches in manufacturing since Water Shewhart first proposed the use of control charts in 1924. The combination development of big data, cloud computing, and manufacturing reshoring back to Untied States has opened up the opportunities to rethink implementation strategies of SPC for manufacturing. This paper first reviews the history of SPC development in traditional manufacturing environments and then contrasts it with the opportunities presented in big data era. Five SPC implementation approaches are proposed based on the opportunities identified.

Copyright © 2017 by ASME



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