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Publications (10 of 111) Show all publications
Lindström, J., Lejon, E., Kyösti, P., Mecella, M., Heutelbeck, D., Hemmje, M., . . . Gunnarsson, B. (2019). Towards intelligent and sustainable production systems with a zero-defect manufacturing approach in an Industry4.0 context. In: Edited by Peter Butala, Edvard Govekar, Rok Vrabič (Ed.), Procedia CIRP, vol 81: . Paper presented at 52nd CIRP Conference on Manufacturing Systems (CMS), Ljubljana, Slovenia, June 12-14, 2019 (pp. 880-885). Elsevier, 81
Open this publication in new window or tab >>Towards intelligent and sustainable production systems with a zero-defect manufacturing approach in an Industry4.0 context
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2019 (English)In: Procedia CIRP, vol 81 / [ed] Edited by Peter Butala, Edvard Govekar, Rok Vrabič, Elsevier, 2019, Vol. 81, p. 880-885Conference paper, Published paper (Refereed)
Abstract [en]

The paper addresses intelligent and sustainable production achieved through combination and integration of online predictive maintenance, monitoring of process parameters and continuous quality control of both input materials and output from the process. This enables production systems, within both manufacturing and process industries, to move towards zero-defect manufacturing. Such a zero-defect manufacturing approach allows for earlier identification of problems or issues, which will or already negatively affect the output. The paper outlines the first part of the second cycle of an action research effort at Gestamp HardTech AB in Sweden, whose objective is to keep its position as a world-leading provider of press-hardened vehicle parts. In order to fully implement the zero-defect manufacturing approach, 4-6 action research cycles are expected to be needed in order to iteratively refine the approach. During the first cycle, various methods and solutions for some of the individual issues/problems have been conceptualized, realized and initially tested. The selected design criteria for the action research efforts were: simplicity, low cost, robustness, high-quality output and future-proofing. The result from the research in the second cycle so far is an action plan for the technical change and a set of challenges/problems which need additional investigation.

Place, publisher, year, edition, pages
Elsevier, 2019
Series
Procedia CIRP, vol 81, ISSN 2212-8271
Keywords
continuous quality controlI, Industry4.0, intelligent, online predictive maintenance, production, sustainable, zero-defect manufacturing
National Category
Engineering and Technology Information Systems, Social aspects Control Engineering Applied Mechanics
Research subject
Information systems; Experimental Mechanics; Control Engineering
Identifiers
urn:nbn:se:ltu:diva-75114 (URN)10.1016/j.procir.2019.03.218 (DOI)
Conference
52nd CIRP Conference on Manufacturing Systems (CMS), Ljubljana, Slovenia, June 12-14, 2019
Available from: 2019-06-28 Created: 2019-06-28 Last updated: 2019-07-08Bibliographically approved
Loureiro, T., Rämä, M., Sterling, R., Cozzini, M., Vinyals, M., Descamps, M., . . . Geyer, P. (2018). District Energy Systems: A Collaborative Exchange of Results on Planning, Operation and Modelling for Energy Efficiency. In: : . Paper presented at Sustainable Places 2018 (SP 2018), 27-29 June 2018, Aix-les Bains, France (pp. 1127-1131). Basel, Switzerland: MDPI, 2(15)
Open this publication in new window or tab >>District Energy Systems: A Collaborative Exchange of Results on Planning, Operation and Modelling for Energy Efficiency
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2018 (English)Conference paper, Published paper (Other academic)
Abstract [en]

Workshop organized by INDIGO project as a collaborative activity among EU funded projects in the area of District Heating and Cooling. The objective of the workshop was twofold: (1) to create a cluster of European funded projects working in the area of District Energy Systems; and (2) to create a networking opportunity in which to share experiences on the results and difficulties of the researches, and to identify synergies.

Place, publisher, year, edition, pages
Basel, Switzerland: MDPI, 2018. p. 5
Keywords
district energy systems, district heating and cooling, energy efficiency, planning, modelling
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-71415 (URN)10.3390/proceedings2151127 (DOI)
Conference
Sustainable Places 2018 (SP 2018), 27-29 June 2018, Aix-les Bains, France
Projects
OPTi
Available from: 2018-11-01 Created: 2018-11-01 Last updated: 2018-11-06Bibliographically approved
Castaño Arranz, M., Birk, W. & Kadhim, A. (2018). On Guided and Automatic Control Configuration Selection. In: IEEE International Conference on Emerging Technologies and Factory Automation (ETFA): . Paper presented at 22nd IEEE International Conference on Emerging Technologies And Factory Automation (ETFA), Limassol, Cyprus, 12-15 September 2017. Piscataway, Nj: Institute of Electrical and Electronics Engineers (IEEE), F134116
Open this publication in new window or tab >>On Guided and Automatic Control Configuration Selection
2018 (English)In: IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Piscataway, Nj: Institute of Electrical and Electronics Engineers (IEEE), 2018, Vol. F134116Conference paper, Published paper (Refereed)
Abstract [en]

This paper discusses the guided and automatic control configuration selection in large scale complex systems. Due to the trend of increasesd level of automation and connectedness which is promoted by the Industry 4.0 strategy and supported by technologies relating to cyber-physical systems and the industrial internet of things, selecting appropriate control strategies becomes increasingly important and complex. This is especially important as a control strategies will limit the achievable performance of the process system, and there are  trade-offs between complexity of the control strategies, achievable performance, vulnerability and maintainability.

The paper reviews the state of the art of methodologies that support the practitioners in taking decisions on control strategies, where two main approaches are considered, the guided one and a fully automatic one. It is shown how both approached can be conducted and examples are used to clarify the selection process.

Abstract [en]

Selecting appropriate control configurations becomes increasingly important and complex. This is due to the trend of increased level of automation and connectedness which is promoted by Industry 4.0 and supported by technologies relating to cyber-physical systems and the industrial internet of things. In this scenario, there are trade-offs between simplicity of the control configurations, achievable performance, vulnerability and maintainability. The paper reviews different state of the art tools before integrating them in guidelines and in automatic methods that support the practitioners in the design on control configurations.

Place, publisher, year, edition, pages
Piscataway, Nj: Institute of Electrical and Electronics Engineers (IEEE), 2018
Series
IEEE International Conference on Emerging Technologies and Factory Automation-ETFA, ISSN 1946-0740
Keywords
automatic control configuration selection, decentralized control, interaction measures, sparse control
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-63153 (URN)10.1109/ETFA.2017.8247700 (DOI)000427812000135 ()2-s2.0-85044482354 (Scopus ID)978-1-5090-6505-9 (ISBN)
Conference
22nd IEEE International Conference on Emerging Technologies And Factory Automation (ETFA), Limassol, Cyprus, 12-15 September 2017
Projects
OPTi Optimisation of District Heating Cooling systems, OPTiIntegrated Process Control based on Distributed In-Situ Sensors into Raw Material and Energy Feedstock, DISIREWARP
Funder
VINNOVAEU, Horizon 2020, 649796EU, Horizon 2020, 636834
Available from: 2017-04-25 Created: 2017-04-25 Last updated: 2018-05-29Bibliographically approved
Castaño Arranz, M., Birk, W. & Nikolakopoulos, G. (2017). A Survey on Control Configuration Selection and New Challenges in Relation to Wireless Sensor and Actuator Networks. Paper presented at 20th IFAC World Congress, Toulouse, France, 9-14 July 2017. IFAC-PapersOnLine, 50(1), 8810-8825
Open this publication in new window or tab >>A Survey on Control Configuration Selection and New Challenges in Relation to Wireless Sensor and Actuator Networks
2017 (English)In: IFAC-PapersOnLine, ISSN 1045-0823, E-ISSN 1797-318X, Vol. 50, no 1, p. 8810-8825Article in journal (Refereed) Published
Abstract [en]

This survey on Control Configuration Selection (CCS) includes methods based on relative gains, gramian-based interaction measures, methods based on optimization schemes, plantwide control, and methods for the reconfiguration of control systems. The CCS problem is discussed, and a set of desirable properties of a CCS method are defined. Open questions and research tracks are discussed, with the focus on new challenges in relation to the emerging area of Wireless Sensors and Actuator Networks.

Place, publisher, year, edition, pages
Elsevier, 2017
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-66198 (URN)10.1016/j.ifacol.2017.08.1536 (DOI)000423964900456 ()
Conference
20th IFAC World Congress, Toulouse, France, 9-14 July 2017
Projects
Integrated Process Control based on Distributed In-Situ Sensors into Raw Material and Energy Feedstock, DISIREOPTi Optimisation of District Heating Cooling systems, OPTi
Funder
EU, Horizon 2020, 649796EU, Horizon 2020, 636834VINNOVA
Note

Konferensartikel i tidskrift

Available from: 2017-10-19 Created: 2017-10-19 Last updated: 2018-05-29Bibliographically approved
Kadhim, A., Castaño Arranz, M. & Birk, W. (2017). Automated Control Configuration Selection Considering System Uncertainties. Industrial & Engineering Chemistry Research, 56(12), 3347-3359
Open this publication in new window or tab >>Automated Control Configuration Selection Considering System Uncertainties
2017 (English)In: Industrial & Engineering Chemistry Research, ISSN 0888-5885, E-ISSN 1520-5045, Vol. 56, no 12, p. 3347-3359Article in journal (Refereed) Published
Abstract [en]

This paper proposes an automated pairing approach for configuration selection of decentralized controllers which considers system uncertainties. Following the Relative Interaction Array (RIA) pairing rules, the optimal control configuration, i.e. the configuration that fits best the pairing rules, is obtained automatically by formulating the control configuration selection problem as an Assignment Problem (AP). In this AP, the associated costs related to each input-output pairing are given by the RIA coefficients. The Push-Pull algorithm is used to solve the AP for the nominal system and to obtain the set of costs for which the resulting configuration remains optimal, also called the perturbation set. The introduction of uncertainty bounds on the RIA-based costs enables the testing of the possible violation of the optimality conditions. Examples to illustrate the proposed approach for a 3×3 system and 4×4 gasifier plant are given.

Place, publisher, year, edition, pages
American Chemical Society (ACS), 2017
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-62421 (URN)10.1021/acs.iecr.6b04035 (DOI)000398248000021 ()2-s2.0-85019961627 (Scopus ID)
Projects
OPTi Optimisation of District Heating Cooling systems, OPTiIntegrated Process Control based on Distributed In-Situ Sensors into Raw Material and Energy Feedstock, DISIRE
Funder
EU, Horizon 2020, 649796EU, Horizon 2020, 636834VINNOVA
Note

Validerad; 2017; Nivå 2; 2017-03-29 (rokbeg)

Available from: 2017-03-10 Created: 2017-03-10 Last updated: 2018-12-14Bibliographically approved
Castaño Arranz, M. (2017). On Guided and Automatic Control Configuration Selection: Application on a Secondary Heating System.
Open this publication in new window or tab >>On Guided and Automatic Control Configuration Selection: Application on a Secondary Heating System
2017 (English)Report (Other academic)
Abstract [en]

This technical report provides supplementary materialto the research paper entitled ”On Guided and AutomaticControl Configuration Selection”, presented at the ETFA 2017.In that paper, different Control Configuration Selection (CCS)tools are reviewed and integrated into guided and automaticCCS methodologies. The guided CCS is a heuristic step-by-stepmethodology to be applied by practitioners, while the automaticCCS methodologies target the adaptation of such heuristicsinto algorithms which can be run in a computer and assist thepractitioners in the decision making. This report summarizesthe results of applying the introduced methodologies to a reallifeprocess: the Secondary Heating System. For an introductorybackground, preliminaries, and details on the methodologies,the reader is referred to the original research paper.

Series
Technical report / Luleå University of Technology, ISSN 1402-1536
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-65819 (URN)978-91-7583-981-3 (ISBN)
Projects
WARPDISIREOPTi
Available from: 2017-09-25 Created: 2017-09-25 Last updated: 2018-05-08Bibliographically approved
Castaño Arranz, M. & Birk, W. (2017). Online Automatic and Robust Control Configuration Selection. In: 2017 25th Mediterranean Conference on Control and Automation, MED 2017: . Paper presented at 25th Mediterranean Conference on Control and Automation, MED 2017, University of Malta, Valletta, Malta, 3-6 July 2017 (pp. 1367-1372). Piscataway, NJ: IEEE, Article ID 7984309.
Open this publication in new window or tab >>Online Automatic and Robust Control Configuration Selection
2017 (English)In: 2017 25th Mediterranean Conference on Control and Automation, MED 2017, Piscataway, NJ: IEEE, 2017, p. 1367-1372, article id 7984309Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a complete method for automatic and robust control configuration selection for linear systems which relies upon acquired process data under gaussian noise excitation.

The selection of the configuration  is based on the estimation of the Interaction Measure named Participation Matrix. This estimation is derived with uncertainty bounds, which allows to  determine online whether the uncertainty is sufficiently low to derive a robust decision on the control configuration to be used or if the uncertainty should be reduced  by e.g. prolonging the experiment to obtain more data.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE, 2017
Series
Mediterranean Conference on Control and Automation, ISSN 2325-369X
Keywords
Interaction Measures, Control Configuration Selection, Control Structure Selection, Robust Control, Decentralized Control
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-63040 (URN)10.1109/MED.2017.7984309 (DOI)000426926300224 ()2-s2.0-85027838178 (Scopus ID)978-1-5090-4533-4 (ISBN)
Conference
25th Mediterranean Conference on Control and Automation, MED 2017, University of Malta, Valletta, Malta, 3-6 July 2017
Projects
Integrated Process Control based on Distributed In-Situ Sensors into Raw Material and Energy Feedstock, DISIREOPTi Optimisation of District Heating Cooling systems, OPTi
Funder
EU, Horizon 2020, 636834EU, Horizon 2020, 649796VINNOVA
Available from: 2017-04-17 Created: 2017-04-17 Last updated: 2018-05-29Bibliographically approved
Castaño Arranz, M. & Birk, W. (2017). Prediction Error based Interaction Measure for Control Configuration Selection in Linear and Nonlinear Systems. In: : . Paper presented at 10th IFAC International Symposium onAdvanced Control of Chemical Processes, (ADCHEM 2018), Shenyang, Liaoning, China, July 25 - 27, 2018 (pp. 446-451). Elsevier, 51
Open this publication in new window or tab >>Prediction Error based Interaction Measure for Control Configuration Selection in Linear and Nonlinear Systems
2017 (English)Conference paper, Published paper (Refereed)
Abstract [en]

This paper introduces an interaction measure, which can be applied both to linear and non-linear systems. The measure is based on the prediction error of the structurally reduced model and is denoted Prediction Error Index Array (PEIA). The linear PEIA is constructed as an extension of previous results using the $\mathcal{H}_2$-norm. The non-linear PEIA is an extension for systems represented by a model in the form of Volterra series. Additionally, the paper gives an interpretation of both linear and nonlinear PEIA as the fraction of the power of the output signal which is expressed by the reduced model resulting from  the  control configuration selection. Several examples are used to illustrate and compare the interaction measure with established methodologies, like the relative gain array, participation matrix, and Hankel Interaction Index array.

Place, publisher, year, edition, pages
Elsevier, 2017
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-66326 (URN)10.1016/j.ifacol.2018.09.341 (DOI)000446604800077 ()2-s2.0-85054391486 (Scopus ID)
Conference
10th IFAC International Symposium onAdvanced Control of Chemical Processes, (ADCHEM 2018), Shenyang, Liaoning, China, July 25 - 27, 2018
Projects
OPTiWARPDISIRE
Available from: 2017-10-31 Created: 2017-10-31 Last updated: 2018-10-22Bibliographically approved
Garmabaki, A., Birk, W. & Lindström, J. (2017). Software Fault Detection in Control Systems (ed.). In: (Ed.), Walls L.,Revie M.,Bedford T (Ed.), Risk, Reliability and Safety: Innovating Theory and Practice - Proceedings of the 26th European Safety and Reliability Conference, ESREL 2016. Paper presented at European Safety and Reliability Conference : European Safety and Reliability Conference 25/09/2016 - 29/09/2016 (pp. 2006-2012). CRC Press
Open this publication in new window or tab >>Software Fault Detection in Control Systems
2017 (English)In: Risk, Reliability and Safety: Innovating Theory and Practice - Proceedings of the 26th European Safety and Reliability Conference, ESREL 2016 / [ed] Walls L.,Revie M.,Bedford T, CRC Press, 2017, p. 2006-2012Conference paper, Published paper (Refereed)
Abstract [en]

Fault detection in the software of control systems is a difficult task. In largely interconnected systems, not only the individual performance of one channel, but also its interaction with other components, must be considered. In this conceptual paper, we outline a new maintenance concept for the detection of software faults in control systems. The concept includes two approaches, morning gymnastics test and envelope analysis. The morning gymnastics test generates data for a baseline of the current operational abilities in contrast to the specified abilities and should be applied when feasible in continuous production systems. The test integrates historical and new sets of data to track degradation trends. Envelope analysis can be performed to detect operational anomalies and is based on subsequent deep analysis to distinguish software and hardware faults from each other. By using the envelope analysis it is possible to identify failures and disturbances affecting the control system. Thus, the proposed maintenance concept may facilitate detection and identification of potential failures in critical automated system.

Place, publisher, year, edition, pages
CRC Press, 2017
Keywords
maintenance, Software Fault Detection, Control Systems, morning gymnastics, envelope analysis, anomalies detection, Information technology - Computer science, Information technology - Automatic control, Informationsteknik - Datorvetenskap, Informationsteknik - Reglerteknik
National Category
Other Civil Engineering Control Engineering
Research subject
Operation and Maintenance; Control Engineering
Identifiers
urn:nbn:se:ltu:diva-32585 (URN)000414164700286 ()2-s2.0-85016227621 (Scopus ID)71fba7cc-e4c6-4bcb-88e5-5fbe41bd9200 (Local ID)9781138029972 (ISBN)978-1-315-37498-7 (ISBN)71fba7cc-e4c6-4bcb-88e5-5fbe41bd9200 (Archive number)71fba7cc-e4c6-4bcb-88e5-5fbe41bd9200 (OAI)
Conference
European Safety and Reliability Conference : European Safety and Reliability Conference 25/09/2016 - 29/09/2016
Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2018-05-07Bibliographically approved
Kadhim, A., Birk, W. & Castaño Arranz, M. (2016). Dynamic Relative Gain Array Estimation using Local Polynomial Approximation Approach. Modeling, Identification and Control, 37(4), 247-259
Open this publication in new window or tab >>Dynamic Relative Gain Array Estimation using Local Polynomial Approximation Approach
2016 (English)In: Modeling, Identification and Control, ISSN 0332-7353, E-ISSN 1890-1328, Vol. 37, no 4, p. 247-259Article in journal (Refereed) Published
Abstract [en]

This article presents a procedure that utilizes the local polynomial approximation approach in the estimation of the Dynamic Relative Gain Array (DRGA) matrix and its uncertainty bounds for weakly nonlinear systems. This procedure offers enhanced frequency resolution and noise reduction when random excitation is used. It also allows separation of nonlinear distortions with shorter measuring time when multisine excitation is imposed. The procedure is illustrated using the well-known quadruple tank process as a case study in simulation and in real life. Besides, a comparison with the pairing results of the static RGA, nonlinear RGA and DRGA based on linearized quadruple tank model for different simulation cases is performed.

National Category
Control Engineering
Research subject
Control Engineering
Identifiers
urn:nbn:se:ltu:diva-61818 (URN)10.4173/mic.2016.4.5 (DOI)000391206900005 ()2-s2.0-85013356890 (Scopus ID)
Projects
Integrated Process Control based on Distributed In-Situ Sensors into Raw Material and Energy Feedstock, DISIREOPTi Optimisation of District Heating Cooling systems, OPTi
Funder
EU, Horizon 2020, 636834EU, Horizon 2020, 649796
Note

Validerad; 2017; Nivå 2; 2017-02-03 (andbra)

Available from: 2017-02-03 Created: 2017-02-03 Last updated: 2018-07-10Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-5888-8626

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