Journal article
Statistical monitoring performance for startup operations in a feedback control system
Quality and reliability engineering international, Vol.17(5), pp.379-390
09/2001
DOI: 10.1002/qre.421
Abstract
Previously, it has been held that statistical process control (SPC) and engineering process control (EPC) were two distinct domains for process improvement. However, we specifically consider the impact for integrating the two approaches on a first-order dynamic system with ARIMA disturbances. We show how to model and analyze this system over a range of practical conditions. Our work results in a set of response surfaces that characterize the performance of the integrated design. We also compare these results to the case where the SPC and EPC policies are applied separately. In general, we find that the EPC approach performs best in terms of minimizing error, but that we can reduce the number and magnitude of adjustments using the integrated monitoring and control approach. This work also further supports our earlier findings that the integrated design is effective on complex dynamic systems during the initial transient or startup period. Copyright © 2001 John Wiley & Sons, Ltd.
Details
- Title: Subtitle
- Statistical monitoring performance for startup operations in a feedback control system
- Creators
- Harriet Black Nembhard - Department of Industrial Engineering, University of Wisconsin-Madison, 1513 University Ave., Madison, WI 53706, USAChristina M Mastrangelo - Department of Systems Engineering, University of Virginia, Thorton Hall, Charlottesville, VA 22903, USAMing Shu Kao - Department of Industrial Engineering, University of Wisconsin-Madison, 1513 University Ave., Madison, WI 53706, USA
- Resource Type
- Journal article
- Publication Details
- Quality and reliability engineering international, Vol.17(5), pp.379-390
- Publisher
- John Wiley & Sons, Ltd
- DOI
- 10.1002/qre.421
- ISSN
- 0748-8017
- eISSN
- 1099-1638
- Number of pages
- 12
- Language
- English
- Date published
- 09/2001
- Academic Unit
- Industrial and Systems Engineering; Engineering Administration
- Record Identifier
- 9984121962602771
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