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Statistical Process Control in Manufacturing

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Encyclopedia of Systems and Control

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Abstract

Statistical process control (SPC) has been successfully utilized for process monitoring and variation reduction in manufacturing applications. This entry aims to review some of the important monitoring methods. We discuss fundamental process monitoring topics including Shewhart’s model, \(\bar X\) and R control charts, EWMA and CUSUM charts for monitoring small process shifts, process monitoring for autocorrelated data, and integration of statistical and engineering (or automatic) control techniques. We also illustrate the application of SPC in the more recently emerging areas including monitoring profiles, surfaces, and point cloud data sets in manufacturing. The goal is to provide readers from control theory, mechanical engineering, and electrical engineering an expository overview of the key topics in statistical process control.

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Author information

Authors and Affiliations

  1. Department of Industrial and Manufacturing Engineering, High Performance Materials Institute Florida A&M University, Florida State University, Tallahassee, FL, USA

    O. Arda Vanli

  2. Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, PA, USA

    Enrique Del Castillo

Authors
  1. O. Arda Vanli
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  2. Enrique Del Castillo
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Corresponding author

Correspondence to O. Arda Vanli .

Editor information

Editors and Affiliations

  1. Electrical and Computer Engineering, Boston University, Boston, MA, USA

    John Baillieul

  2. Automation and Control Solutions, Honeywell, Golden Valley, MN, USA

    Tariq Samad

Section Editor information

  1. Mechanical Engineering Department, University of Michigan, Ann Arbor, Michigan, USA

    Dawn Tilbury

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Vanli, O.A., Castillo, E.D. (2019). Statistical Process Control in Manufacturing. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5102-9_258-2

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  • DOI: https://doi.org/10.1007/978-1-4471-5102-9_258-2

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-5102-9

  • Online ISBN: 978-1-4471-5102-9

  • eBook Packages: Springer Reference EngineeringReference Module Computer Science and Engineering

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Chapter history

  1. Latest

    Statistical Process Control in Manufacturing
    Published:
    09 December 2019

    DOI: https://doi.org/10.1007/978-1-4471-5102-9_258-2

  2. Original

    Statistical Process Control in Manufacturing
    Published:
    05 November 2014

    DOI: https://doi.org/10.1007/978-1-4471-5102-9_258-1

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