Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Adapting Experimental and Monitoring Methods for Continuous Processes under Feedback Control: Challenges, Examples, and Tools
Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering.
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 [en]
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: urn:nbn:se:ltu:diva-74661ISBN: 978-91-7790-411-3 (print)ISBN: 978-91-7790-412-0 (electronic)OAI: oai:DiVA.org:ltu-74661DiVA, id: diva2:1326463
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: 2019-09-03Bibliographically approved
List of papers
1. Managerial implications for improvingcontinuous production processes
Open this publication in new window or tab >>Managerial implications for improvingcontinuous production processes
2017 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Data analytics remains essential for process improvement and optimization. Statistical process control and design of experiments are among the most powerful process and product improvement methods available. However, continuous process environments challenge the application of these methods. In this article, we highlight SPC and DoE implementation challenges described in the literature for managers, researchers and practitioners interested in continuous production process improvement. The results may help managers support the implementation of these methods and make researchers and practitioners aware of methodological challenges in continuous process environments.

Keywords
Productivity, Statistical tools, Continuous processes
National Category
Engineering and Technology Reliability and Maintenance
Research subject
Quality Technology and Management
Identifiers
urn:nbn:se:ltu:diva-65568 (URN)
Conference
24th EurOMA Conference, Edinburgh, July 1-5, 2017
Projects
Statistical Methods for Improving Continuous Production
Funder
Swedish Research Council, 4731241
Available from: 2017-09-11 Created: 2017-09-11 Last updated: 2019-06-18Bibliographically approved
2. Exploring the Use of Design of Experiments in Industrial Processes Operating Under Closed-Loop Control
Open this publication in new window or tab >>Exploring the Use of Design of Experiments in Industrial Processes Operating Under Closed-Loop Control
2017 (English)In: Quality and Reliability Engineering International, ISSN 0748-8017, E-ISSN 1099-1638, Vol. 33, no 7, p. 1601-1614Article in journal (Refereed) Published
Abstract [en]

Industrial manufacturing processes often operate under closed-loop control, where automation aims to keep important process variables at their set-points. In process industries such as pulp, paper, chemical and steel plants, it is often hard to find production processes operating in open loop. Instead, closed-loop control systems will actively attempt to minimize the impact of process disturbances. However, we argue that an implicit assumption in most experimental investigations is that the studied system is open loop, allowing the experimental factors to freely affect the important system responses. This scenario is typically not found in process industries. The purpose of this article is therefore to explore issues of experimental design and analysis in processes operating under closed-loop control and to illustrate how Design of Experiments can help in improving and optimizing such processes. The Tennessee Eastman challenge process simulator is used as a test-bed to highlight two experimental scenarios. The first scenario explores the impact of experimental factors that may be considered as disturbances in the closed-loop system. The second scenario exemplifies a screening design using the set-points of controllers as experimental factors. We provide examples of how to analyze the two scenarios

Place, publisher, year, edition, pages
John Wiley & Sons, 2017
National Category
Reliability and Maintenance
Research subject
Quality Technology and Management
Identifiers
urn:nbn:se:ltu:diva-61872 (URN)10.1002/qre.2128 (DOI)000413906100024 ()2-s2.0-85012952363 (Scopus ID)
Note

Validerad;2017;Nivå 2;2017-11-03 (andbra)

Available from: 2017-02-08 Created: 2017-02-08 Last updated: 2019-06-18Bibliographically approved
3. The Revised Tennessee Eastman Process Simulator as Testbed for SPC and DoE Methods
Open this publication in new window or tab >>The Revised Tennessee Eastman Process Simulator as Testbed for SPC and DoE Methods
2019 (English)In: Quality Engineering, ISSN 0898-2112, E-ISSN 1532-4222, Vol. 31, no 2, p. 212-229Article in journal (Refereed) Published
Abstract [en]

Engineering process control and high-dimensional, time-dependent data present great methodological challenges when applying statistical process control (SPC) and design of experiments (DoE) in continuous industrial processes. Process simulators with an ability to mimic these challenges are instrumental in research and education. This article focuses on the revised Tennessee Eastman process simulator providing guidelines for its use as a testbed for SPC and DoE methods. We provide flowcharts that can support new users to get started in the Simulink/Matlab framework, and illustrate how to run stochastic simulations for SPC and DoE applications using the Tennessee Eastman process.

Place, publisher, year, edition, pages
Taylor & Francis, 2019
Keywords
Simulation, Tutorial, Statistical process control, Design of experiments, Engineering process control, Closed-loop
National Category
Reliability and Maintenance
Research subject
Quality technology and logistics
Identifiers
urn:nbn:se:ltu:diva-66255 (URN)10.1080/08982112.2018.1461905 (DOI)000468617000002 ()2-s2.0-85066129240 (Scopus ID)
Projects
Statistical Methods for Improving Continuous Production
Note

Validerad;2019;Nivå 2;2019-06-11 (johcin)

Available from: 2017-10-25 Created: 2017-10-25 Last updated: 2019-06-18Bibliographically approved
4. On Monitoring Industrial Processes under Feedback Control
Open this publication in new window or tab >>On Monitoring Industrial Processes under Feedback Control
Show others...
(English)In: Article in journal (Refereed) Submitted
Keywords
engineering process control (EPC), statistical process control (SPC), control charts, proportional-integral-derivative (PID), disturbance signatures.
National Category
Other Engineering and Technologies
Research subject
Quality Technology & Management
Identifiers
urn:nbn:se:ltu:diva-74657 (URN)
Available from: 2019-06-18 Created: 2019-06-18 Last updated: 2019-06-18
5. A Two-Step Monitoring Procedure for Knowledge Discovery in Industrial Processes under Feedback Control
Open this publication in new window or tab >>A Two-Step Monitoring Procedure for Knowledge Discovery in Industrial Processes under Feedback Control
(English)In: Article in journal (Refereed) Submitted
Keywords
multivariate processes, multivariate statistical process control, engineering process control, latent structure methods, enhanced process understanding
National Category
Other Engineering and Technologies
Research subject
Quality technology and logistics; Quality Technology & Management
Identifiers
urn:nbn:se:ltu:diva-74659 (URN)
Available from: 2019-06-18 Created: 2019-06-18 Last updated: 2019-06-18

Open Access in DiVA

fulltext(9239 kB)47 downloads
File information
File name FULLTEXT01.pdfFile size 9239 kBChecksum SHA-512
55ed123d3a37a8c59f61762449449f75b00403f6eb0de659127b47aaa1dea721d250d3df29761c8bed1f1ff86e6ebfa4d56640da4c16add845aadaabf41f38c5
Type fulltextMimetype application/pdf

Authority records BETA

Capaci, Francesca

Search in DiVA

By author/editor
Capaci, Francesca
By organisation
Business Administration and Industrial Engineering
Other Engineering and Technologies

Search outside of DiVA

GoogleGoogle Scholar
Total: 47 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 135 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf