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The Revised Tennessee Eastman Process Simulator as Testbed for SPC and DoE Methods
Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle, Industriell Ekonomi.
Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle, Industriell Ekonomi.ORCID-id: 0000-0003-1473-3670
Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle, Industriell Ekonomi. Technical university of Denmark .ORCID-id: 0000-0003-4222-9631
Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle, Industriell Ekonomi.ORCID-id: 0000-0003-3911-8009
2019 (Engelska)Ingår i: Quality Engineering, ISSN 0898-2112, E-ISSN 1532-4222, Vol. 31, nr 2, s. 212-229Artikel i tidskrift (Refereegranskat) 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.

Ort, förlag, år, upplaga, sidor
Taylor & Francis, 2019. Vol. 31, nr 2, s. 212-229
Nyckelord [en]
Simulation, Tutorial, Statistical process control, Design of experiments, Engineering process control, Closed-loop
Nationell ämneskategori
Tillförlitlighets- och kvalitetsteknik
Forskningsämne
Kvalitetsteknik och logistik
Identifikatorer
URN: urn:nbn:se:ltu:diva-66255DOI: 10.1080/08982112.2018.1461905ISI: 000468617000002Scopus ID: 2-s2.0-85066129240OAI: oai:DiVA.org:ltu-66255DiVA, id: diva2:1152532
Projekt
Statistical Methods for Improving Continuous Production
Anmärkning

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

Tillgänglig från: 2017-10-25 Skapad: 2017-10-25 Senast uppdaterad: 2019-06-18Bibliografiskt granskad
Ingår i avhandling
1. Contributions to the Use of Statistical Methods for Improving Continuous Production
Öppna denna publikation i ny flik eller fönster >>Contributions to the Use of Statistical Methods for Improving Continuous Production
2017 (Engelska)Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

Complexity of production processes, high computing capabilities, and massive datasets characterize today’s manufacturing environments, such as those of continuous andbatch production industries. Continuous production has spread gradually acrossdifferent industries, covering a significant part of today’s production. Commonconsumer goods such as food, drugs, and cosmetics, and industrial goods such as iron,chemicals, oil, and ore come from continuous processes. To stay competitive intoday’s market requires constant process improvements in terms of both effectivenessand efficiency. Statistical process control (SPC) and design of experiments (DoE)techniques can play an important role in this improvement strategy. SPC attempts toreduce process variation by eliminating assignable causes, while DoE is used toimprove products and processes by systematic experimentation and analysis. However,special issues emerge when applying these methods in continuous process settings.Highly automated and computerized processes provide an exorbitant amount ofserially dependent and cross-correlated data, which may be difficult to analyzesimultaneously. Time series data, transition times, and closed-loop operation areexamples of additional challenges that the analyst faces.The overall objective of this thesis is to contribute to using of statisticalmethods, namely SPC and DoE methods, to improve continuous production.Specifically, this research serves two aims: [1] to explore, identify, and outlinepotential challenges when applying SPC and DoE in continuous processes, and [2] topropose simulation tools and new or adapted methods to overcome the identifiedchallenges.The results are summarized in three appended papers. Through a literaturereview, Paper A outlines SPC and DoE implementation challenges for managers,researchers, and practitioners. For example, problems due to process transitions, themultivariate nature of data, serial correlation, and the presence of engineering processcontrol (EPC) are discussed. Paper B further explores one of the DoE challengesidentified in Paper A. Specifically, Paper B describes issues and potential strategieswhen designing and analyzing experiments in processes operating under closed-loopcontrol. Two simulated examples in the Tennessee Eastman (TE) process simulatorshow the benefits of using DoE techniques to improve and optimize such industrialprocesses. Finally, Paper C provides guidelines, using flow charts, on how to use thecontinuous process simulator, “The revised TE process simulator,” run with adecentralized control strategy as a test bed for developing SPC and DoE methods incontinuous processes. Simulated SPC and DoE examples are also discussed.

Ort, förlag, år, upplaga, sidor
Luleå: Luleå University of Technology, 2017. s. 109
Serie
Licentiate thesis / Luleå University of Technology, ISSN 1402-1757
Nyckelord
Process industry, Continuous process, Statistical process control, Design of experiments, Process improvements, Simulation tool, Engineering process control
Nationell ämneskategori
Annan teknik
Forskningsämne
Kvalitetsteknik
Identifikatorer
urn:nbn:se:ltu:diva-66256 (URN)978-91-7583-996-7 (ISBN)978-91-7583-997-4 (ISBN)
Presentation
2017-11-27, A109, Luleå University of Technology, Luleå, 13:00 (Engelska)
Opponent
Handledare
Forskningsfinansiär
Vetenskapsrådet, 4731241
Tillgänglig från: 2017-10-25 Skapad: 2017-10-25 Senast uppdaterad: 2017-11-27Bibliografiskt granskad
2. Adapting Experimental and Monitoring Methods for Continuous Processes under Feedback Control: Challenges, Examples, and Tools
Öppna denna publikation i ny flik eller fönster >>Adapting Experimental and Monitoring Methods for Continuous Processes under Feedback Control: Challenges, Examples, and Tools
2019 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
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.

Ort, förlag, år, upplaga, sidor
Luleå: Luleå University of Technology, 2019
Serie
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
Nyckelord
Continuous process, Statistical process control, Design of experiments, Engineering process control, Quality improvement, Simulation tools.
Nationell ämneskategori
Annan teknik
Forskningsämne
Kvalitetsteknik och logistik; Kvalitetsteknik
Identifikatorer
urn:nbn:se:ltu:diva-74661 (URN)978-91-7790-411-3 (ISBN)978-91-7790-412-0 (ISBN)
Disputation
2019-09-27, A109, Luleå University of Technology, Lulea, 09:00 (Engelska)
Opponent
Handledare
Tillgänglig från: 2019-06-19 Skapad: 2019-06-18 Senast uppdaterad: 2019-09-03Bibliografiskt granskad

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