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On Monitoring Industrial Processes under Feedback Control
Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering.ORCID iD: 0000-0003-0740-2531
Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering. (Quality Technology and Management)ORCID iD: 0000-0003-1473-3670
Department of Chemical Engineering, University of California, Davis, California, USA.
Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering.ORCID iD: 0000-0003-3911-8009
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2020 (English)In: Quality and Reliability Engineering International, ISSN 0748-8017, E-ISSN 1099-1638, Vol. 36, no 8, p. 2720-2737Article in journal (Refereed) Published
Abstract [en]

The concurrent use of statistical process control and engineering process con-trol involves monitoring manipulated and controlled variables. One multivari-ate control chart may handle the statistical monitoring of all variables, butobserving the manipulated and controlled variables in separate control chartsmay improve understanding of how disturbances and the controller perfor-mance affect the process. In this article, we illustrate how step and ramp dis-turbances manifest themselves in a single-input–single-output system bystudying their resulting signatures in the controlled and manipulated variables.The system is controlled by variations of the widely used proportional-integral-derivative(PID) control scheme. Implications for applying control charts forthese scenarios are discussed.

Place, publisher, year, edition, pages
John Wiley & Sons, 2020. Vol. 36, no 8, p. 2720-2737
Keywords [en]
control charts, disturbance signatures, engineering process control (EPC), proportional-integral-derivative (PID), statistical process control (SPC)
National Category
Reliability and Maintenance
Research subject
Quality technology and logistics
Identifiers
URN: urn:nbn:se:ltu:diva-74657DOI: 10.1002/qre.2676ISI: 000544343400001Scopus ID: 2-s2.0-85087166819OAI: oai:DiVA.org:ltu-74657DiVA, id: diva2:1326457
Note

Validerad;2020;Nivå 2;2020-11-09 (johcin)

Available from: 2019-06-18 Created: 2019-06-18 Last updated: 2024-03-27Bibliographically approved
In thesis
1. Adapting Experimental and Monitoring Methods for Continuous Processes under Feedback Control: Challenges, Examples, and Tools
Open this publication in new window or tab >>Adapting Experimental and Monitoring Methods for Continuous Processes under Feedback Control: Challenges, Examples, and Tools
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Continuous production covers a significant part of today’s industrial manufacturing. Consumer goods purchased on a frequent basis, such as food, drugs, and cosmetics, and capital goods such as iron, chemicals, oil, and ore come through continuous processes. Statistical process control (SPC) and design of experiments (DoE) play important roles as quality control and product and process improvement methods. SPC reduces product and process variation by eliminating assignable causes, while DoE shows how products and processes may be improved through systematic experimentation and analysis. Special issues emerge when applying these methods to continuous process settings, such as the need to simultaneously analyze massive time series of autocorrelated and cross-correlated data. Another important characteristic of most continuous processes is that they operate under engineering process control (EPC), as in the case of feedback controllers. Feedback controllers transform processes into closed-loop systems and thereby increase the process and analysis complexity and application of SPC and DoE methods that need to be adapted accordingly. For example, the quality characteristics or process variables to be monitored in a control chart or the experimental factors in an experiment need to be chosen considering the presence of feedback controllers.

The main objective of this thesis is to suggest adapted strategies for applying experimental and monitoring methods (namely, DoE and SPC) to continuous processes under feedback control. Specifically, this research aims to [1] identify, explore, and describe the potential challenges when applying SPC and DoE to continuous processes; [2] propose and illustrate new or adapted SPC and DoE methods to address some of the issues raised by the presence of feedback controllers; and [3] suggest potential simulation tools that may be instrumental in SPC and DoE methods development.

The results are summarized in five appended papers. Through a literature review, Paper A outlines the SPC and DoE implementation challenges for managers, researchers, and practitioners. For example, the problems due to process transitions, the multivariate nature of data, serial correlation, and the presence of EPC are discussed. Paper B describes the issues and potential strategies in designing and analyzing experiments on processes operating under closed- loop control. Two simulated examples in the Tennessee Eastman (TE) process simulator show the benefits of using DoE methods to improve these industrial processes. Paper C provides guidelines on how to use the revised TE process simulator under a decentralized control strategy as a testbed for SPC and DoE methods development in continuous processes. Papers D and E discuss the concurrent use of SPC in processes under feedback control. Paper D further illustrates how step and ramp disturbances manifest themselves in single-input single-output processes controlled by variations in the proportional-integral-derivative control and discusses the implications for process monitoring. Paper E describes a two-step monitoring procedure for multivariate processes and explains the process and controller performance when out-of-controlprocess conditions occur.

Place, publisher, year, edition, pages
Luleå: Luleå University of Technology, 2019
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
Keywords
Continuous process, Statistical process control, Design of experiments, Engineering process control, Quality improvement, Simulation tools
National Category
Other Engineering and Technologies
Research subject
Quality technology and logistics; Quality Technology & Management
Identifiers
urn:nbn:se:ltu:diva-74661 (URN)978-91-7790-411-3 (ISBN)978-91-7790-412-0 (ISBN)
Public defence
2019-09-27, A109, Luleå University of Technology, Lulea, 09:00 (English)
Opponent
Supervisors
Available from: 2019-06-19 Created: 2019-06-18 Last updated: 2024-03-27Bibliographically approved

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Capaci, FrancescaVanhatalo, ErikBergquist, BjarneKulahci, Murat

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