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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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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Latest
Statistical Process Control in Manufacturing- Published:
- 09 December 2019
DOI: https://doi.org/10.1007/978-1-4471-5102-9_258-2
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Original
Statistical Process Control in Manufacturing- Published:
- 05 November 2014
DOI: https://doi.org/10.1007/978-1-4471-5102-9_258-1