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Goienetxea Uriarte, AinhoaORCID iD iconorcid.org/0000-0003-4604-6429
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Goienetxea, A., Ng, A. H. .. & Urenda Moris, M. (2019). Bringing together Lean and simulation: a comprehensive review. International Journal of Production Research
Open this publication in new window or tab >>Bringing together Lean and simulation: a comprehensive review
2019 (English)In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588XArticle, review/survey (Refereed) Epub ahead of print
Abstract [en]

Lean is and will still be one of the most popular management philosophies in the Industry 4.0 context and simulation is one of its key technologies. Many authors discuss about the benefits of combining Lean and simulation to better support decision makers in system design and improvement. However, there is a lack of reviews in the domain. Therefore, this paper presents a four-stage comprehensive review and analysis of existing literature on their combination. The aim is to identify the state of the art, existing methods and frameworks for combining Lean and simulation, while also identifying key research perspectives and challenges. The main trends identified are the increased interest in the combination of Lean and simulation in the Industry 4.0 context and in their combination with optimisation, Six Sigma, as well as sustainability. The number of articles in these areas is likely to continue to grow. On the other hand, we highlight six gaps found in the literature regarding the combination of Lean and simulation, which may induce new research opportunities. Existing technical, organisational, as well as people and culture related challenges on the combination of Lean and simulation are also discussed.

Place, publisher, year, edition, pages
Taylor & Francis Group, 2019
Keywords
Lean, simulation, review, framework, discrete event simulation
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-17493 (URN)10.1080/00207543.2019.1643512 (DOI)000477234000001 ()
Funder
Knowledge Foundation
Available from: 2019-08-05 Created: 2019-08-05 Last updated: 2019-08-20Bibliographically approved
Goienetxea Uriarte, A. (2019). Bringing Together Lean, Simulation and Optimization: Defining a framework to support decision-making in system design and improvement. (Doctoral dissertation). Skövde: University of Skövde
Open this publication in new window or tab >>Bringing Together Lean, Simulation and Optimization: Defining a framework to support decision-making in system design and improvement
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The rapid changes in the market including globalization, the requirement for personalizedproducts and services by the customers, shorter product life-cycles, the exponential growthof technological advances, and the demographical changes, will demand organizations toeffectively improve and design their systems in order to survive. This is the actual paradigmcharacterizing the industrial and service sectors. This scenario presents a considerablechallenge to decision makers who will need to decide about how to design and improve amore than ever complex system without compromising the quality of the decision taken.Lean, being a widely applied management philosophy with very powerful principles, itsmethods and tools are static in nature and have some limitations when it comes to the designand improvement of complex and dynamic systems. Some authors have proposed thecombined use of simulation with Lean in order to overcome these limitations. Furthermore,optimization and post-optimization tools coupled to simulation, provide knowledge aboutoptimal or nearly optimal system configurations to choose from. However, even if Leanprinciples, methods and tools, as well as simulation and optimization, pursue the objectiveof supporting organizations regarding system design and improvement, a bilateral approachfor their combination and its benefits have barely been addressed in the literature.Many studies focus only on how specific Lean tools and simulation can be combined, treatingLean purely as a toolbox and not considering how Lean can support the simulation process.The aim of this research is to address this knowledge gap by analyzing the mutualbenefits and presenting a framework for combining Lean, simulation and optimization tobetter support decision makers in system design and improvement where the limitationsof Lean tools and simulation are overcome by their combination. This framework includesa conceptual framework explaining the relationships between the Lean philosophy, methodsand tools with simulation and optimization; the purposes for this combination and stepby step processes to achieve these purposes; the identification of the roles involved in eachprocess; a maturity model providing guidelines on how to implement the framework; existingbarriers for the implementation; and ethical considerations to take into account. Anindustrial handbook has also been written which explains how to deploy the framework.The research has been conducted in three main stages including an analysis of the literatureand the real-world needs, the definition and formulation of the framework, and finally, itsevaluation in real-world projects and with subject matter experts. The main contributionof this research is the reflection provided on the bilateral benefits of the combination, aswell as the defined and evaluated framework, which will support decision makers take qualitydecisions in system design and improvement even in complex scenarios.

Abstract [sv]

De snabba förändringarna på marknaden såsom globalisering, ökat krav på personliga produkteroch tjänster från kunderna, kortare produktlivscykler, tekniska framsteg med exponentielltillväxt samt demografiska förändringar medför ökat krav på att organisationer effektivtförbättrar och utformar sina system. Detta är det nuvarande paradigmet som karaktäriserarindustri- och tjänstesektorerna. Det är ett scenario som utgör en stor utmaningför beslutsfattare, vilka kommer att behöva ta beslut i än mer komplexa system där det blirsvårare att utforma och förbättra system med bibehållen kvalitet. Lean är en allmänt tilllämpadproduktionsfilosofi med kraftfulla principer, med metoder och verktyg som är statiskatill sin natur vilka har begränsningar när det gäller utformning och förbättring avkomplexa och dynamiska system. En del författare har föreslagit den kombinerade användningenav simulering med Lean för att övervinna dessa begränsningar. Dessutom erbjudersimulering kombinerat med optimering och postoptimeringsverktyg genererandet av kunskapom optimala eller nästan optimala systemkonfigurationer. Även om både Lean-principermed dess metoder och verktyg och simulering syftar till att stödja organisationer vidutformning och förbättring av sina system tar litteraturen upp få fördelar med ett kombinerattillvägagångssätt. Flera studier fokuserar endast på hur specifika verktyg inom Leankan kombineras med simulering men behandlar inte hur Lean som filosofi kan stödja simuleringsprocessen.Syftet med denna forskning är att ta itu med denna kunskapsluckagenom att analysera fördelar med kombinationen Lean, simulering och optimering, samtbeskriva hur dess svagheter var för sig kan överbryggas när de kombineras. Resultatet presenterasi ett ramverk med beskrivning av dess genomförande, vilket syftar till att genereraett bättre beslutsstöd vid utformning och förbättring av komplexa och dynamiska system.Ramverket innefattar ett konceptuellt ramverk som förklarar relationerna mellan Lean-filosofin,dess metoder och verktyg, med simulering och optimering; olika ändamål för kombinationenbeskrivs, samt genomgång av steg för steg processer ges för att uppnå dessaändamål; identifiering av de roller som är inblandade i varje process beskrivs; en mognadsmodellpresenteras som ger riktlinjer för hur man implementerar ramverket; befintligahinder för genomförandet och etiska överväganden att ta hänsyn till lyfts också fram. Slutligenhar en industriell handbok skrivits som förklarar hur man ska implementera ramverket.Forskningen har genomförts i tre faser, bland annat en behovsanalys utifrån litteraturenoch verkliga projekt, definitionen av ramverket, och avslutningsvis utvärderas det genomverkliga projekt och med ämnesexperter. Huvudbidraget för denna forskning är reflektionenöver det extra utbytet med kombinationen Lean, simulering och optimering medXIIdess fördelar, vilket bygger på det framtagna ramverket och dess utvärdering. Där ramverkethar för avsikt att stödja beslutsfattare att fatta kvalitetsbeslut vid utformning och identifieringav förbättringar i sina system även i komplexa scenarier.

Place, publisher, year, edition, pages
Skövde: University of Skövde, 2019. p. 430
Series
Dissertation Series ; 29 (2019)
Keywords
lean, simulation, optimization, decision-making
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-17368 (URN)978-91-984918-1-4 (ISBN)
Public defence
2019-08-16, Insikten, Portalen, Skövde, 09:30 (English)
Opponent
Supervisors
Note

List of papers / Delarbete 7 of 8. Goienetxea Uriarte, A., Ng A. H. C. and Urenda Moris, M. (2019). Bringing together Lean and simulation: A comprehensive review. Submitted. 

List of papers / Delarbete 8 of 8. Goienetxea Uriarte, A., Ng A. H. C. and Urenda Moris, M. (2019). Bringing together Lean, simulation and optimization: A reflection and framework proposal. Submitted.

Available from: 2019-07-03 Created: 2019-07-02 Last updated: 2019-07-03Bibliographically approved
Goienetxea Uriarte, A., Sellgren, T., Ng, A. H. C. & Urenda Moris, M. (2019). Introducing simulation and optimization in the Lean continuous improvement standards in an automotive company. In: M. Rabe, A. A. Juan, N. Mustafee, A. Skoogh, S. Jain, B. Johansson (Ed.), Proceedings of the Winter Simulation Conference, Gothenburg, December 9-12, 2018: . Paper presented at Winter Simulation Conference, WSC 2018, Gothenburg, December 9-12, 2018 (pp. 3352-3363). Piscataway, New Jersey: IEEE
Open this publication in new window or tab >>Introducing simulation and optimization in the Lean continuous improvement standards in an automotive company
2019 (English)In: Proceedings of the Winter Simulation Conference, Gothenburg, December 9-12, 2018 / [ed] M. Rabe, A. A. Juan, N. Mustafee, A. Skoogh, S. Jain, B. Johansson, Piscataway, New Jersey: IEEE, 2019, p. 3352-3363Conference paper, Published paper (Refereed)
Abstract [en]

The highly competitive automobile market requires automotive companies to become efficient by continuously improving their production systems. This paper presents a case study where simulationbased optimization (SBO) was employed as a step within a Value Stream Mapping event. The aim of the study was to promote the use of SBO to strengthen the continuous improvement work of the company. The paper presents all the key steps performed in the study, including the challenges faced and a reflection on how to introduce SBO as a powerful tool within the lean continuous improvement standards.

Place, publisher, year, edition, pages
Piscataway, New Jersey: IEEE, 2019
Series
Winter Simulation Conference. Proceedings, ISSN 0891-7736, E-ISSN 1558-4305
Keywords
Lean, simulation, optimization, continuous improvement, automotive
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-16566 (URN)10.1109/WSC.2018.8632403 (DOI)000461414103049 ()2-s2.0-85062610351 (Scopus ID)978-1-5386-6572-5 (ISBN)978-1-5386-6570-1 (ISBN)978-1-5386-6571-8 (ISBN)978-1-5386-6573-2 (ISBN)
Conference
Winter Simulation Conference, WSC 2018, Gothenburg, December 9-12, 2018
Available from: 2019-01-16 Created: 2019-01-16 Last updated: 2019-07-02Bibliographically approved
Goienetxea Uriarte, A. (2018). Bringing together Lean, simulation and optimization in a framework for system design and improvement. In: M. Rabe, A. A. Juan, N. Mustafee, A. Skoogh, S. Jain, B. Johansson (Ed.), Proceedings of the Winter Simulation Conference, Gothenburg, 9-12 December, 2018: . Paper presented at Winter Simulation Conference, Gothenburg, 9-12 December, 2018 (pp. 4132-4133). Piscataway, New Jersey: IEEE
Open this publication in new window or tab >>Bringing together Lean, simulation and optimization in a framework for system design and improvement
2018 (English)In: Proceedings of the Winter Simulation Conference, Gothenburg, 9-12 December, 2018 / [ed] M. Rabe, A. A. Juan, N. Mustafee, A. Skoogh, S. Jain, B. Johansson, Piscataway, New Jersey: IEEE, 2018, p. 4132-4133Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Is it beneficial to combine lean, simulation and optimization? And if so, how can they be combined for decision-making support in system design and improvement? This research proposes a framework that sets the basis for achieving beneficial interactions between the lean philosophy, methods and tools, and simulation-based optimization. A framework that gives the users the possibility to get better system understanding, conduct a deeper system analysis, and attain an optimal system design and improvement, and thereby, get better foundation for sustainable long time improvement. The framework has been tested in several realworld case studies. Moreover, surveys have been conducted to evaluate the perception of subject matter experts about its usefulness, as well as its usability and perceived quality by end users and decision makers, all of them reporting very positive results.

Place, publisher, year, edition, pages
Piscataway, New Jersey: IEEE, 2018
Keywords
Lean, simulation, optimization, framework
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-16567 (URN)
Conference
Winter Simulation Conference, Gothenburg, 9-12 December, 2018
Available from: 2019-01-16 Created: 2019-01-16 Last updated: 2019-06-18Bibliographically approved
Goienetxea Uriarte, A., Ng, A. H. C. & Urenda Moris, M. (2018). Supporting the lean journey with simulation and optimization in the context of Industry 4.0. Paper presented at 8th Swedish Production Symposium, SPS 2018, Stockholm, Sweden, May 16-18, 2018. Procedia Manufacturing, 25, 586-593
Open this publication in new window or tab >>Supporting the lean journey with simulation and optimization in the context of Industry 4.0
2018 (English)In: Procedia Manufacturing, E-ISSN 2351-9789, Vol. 25, p. 586-593Article in journal (Refereed) Published
Abstract [en]

The new industrial revolution brings important changes to organizations that will need to adapt their machines, systems and employees’ competences to sustain their business in a highly competitive market. Management philosophies such as lean will also need to adapt to the improvement possibilities that Industry 4.0 brings. This paper presents a review on the role of lean and simulation in the context of Industry 4.0. Additionally, the paper presents a conceptual framework where simulation and optimization will make the lean approach more efficient, speeding up system improvements and reconfiguration, by means of an enhanced decision-making process and supported organizational learning.

Keywords
Lean, Simulation, Optimization, Industry 4.0, Simulation-based optimization, Decision-making
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-15978 (URN)10.1016/j.promfg.2018.06.097 (DOI)
Conference
8th Swedish Production Symposium, SPS 2018, Stockholm, Sweden, May 16-18, 2018
Available from: 2018-07-16 Created: 2018-07-16 Last updated: 2019-07-02Bibliographically approved
Goienetxea Uriarte, A., Ruiz Zúñiga, E., Urenda Moris, M. & Ng, A. H. C. (2017). How can decision makers be supported in the improvement of an emergency department?: A simulation, optimization and data mining approach. Operations Research for Health Care, 15, 102-122
Open this publication in new window or tab >>How can decision makers be supported in the improvement of an emergency department?: A simulation, optimization and data mining approach
2017 (English)In: Operations Research for Health Care, ISSN 2211-6923, E-ISSN 2211-6931, Vol. 15, p. 102-122Article in journal (Refereed) Published
Abstract [en]

The improvement of emergency department processes involves the need to take into considerationmultiple variables and objectives in a highly dynamic and unpredictable environment, which makes thedecision-making task extremely challenging. The use of different methodologies and tools to support thedecision-making process is therefore a key issue. This article presents a novel approach in healthcarein which Discrete Event Simulation, Simulation-Based Multi-Objective Optimization and Data Miningtechniques are used in combination. This methodology has been applied for a system improvementanalysis in a Swedish emergency department. As a result of the project, the decision makers were providedwith a range of nearly optimal solutions and design rules which reduce considerably the length of stayand waiting times for emergency department patients. These solutions include the optimal number ofresources and the required level of improvement in key processes. The article presents and discussesthe benefits achieved by applying this methodology, which has proven to be remarkably valuable fordecision-making support, with regard to complex healthcare system design and improvement.

Place, publisher, year, edition, pages
Elsevier, 2017
Keywords
Discrete Event Simulation, Simulation-Based Multi-Objective Optimization, Data mining, Decision support, Decision-making, Operational research in health care
National Category
Health Care Service and Management, Health Policy and Services and Health Economy Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering; INF201 Virtual Production Development
Identifiers
urn:nbn:se:his:diva-14404 (URN)10.1016/j.orhc.2017.10.003 (DOI)000415311000010 ()2-s2.0-85032745554 (Scopus ID)
Available from: 2017-11-15 Created: 2017-11-15 Last updated: 2019-07-02Bibliographically approved
Goienetxea Uriarte, A., Ng, A. H. C., Ruiz Zúñiga, E. & Urenda Moris, M. (2017). Improving the Material Flow of a Manufacturing Company via Lean, Simulation and Optimization. In: Proceedings of the International Conference on Industrial Engineering and Engineering Management, IEEM2017: . Paper presented at 2017 International Conference on Industrial Engineering and Engineering Management (IEEM), Singapore, December 10-13, 2017 (pp. 1245-1250). IEEE
Open this publication in new window or tab >>Improving the Material Flow of a Manufacturing Company via Lean, Simulation and Optimization
2017 (English)In: Proceedings of the International Conference on Industrial Engineering and Engineering Management, IEEM2017, IEEE, 2017, p. 1245-1250Conference paper, Published paper (Refereed)
Abstract [en]

Companies are continuously working towards system and process improvement to remain competitive in aglobal market. There are different methods that support companies in the achievement of that goal. This paper presents an innovative process that combines lean, simulation and optimization to improve the material flow of a manufacturing company. A description of each step of the process details the lean tools and principles taken into account, as well as the results achieved by the application of simulation and optimization.The project resulted in an improved layout and material flow that employs an automated guided vehicle. In addition, lean wastes related to transport, inventory levels as well as waiting times were reduced. The utilization of the process that combines lean, simulation and optimization was considered valuable for the success of the project.

Place, publisher, year, edition, pages
IEEE, 2017
Series
IEEE International Conference on Industrial Engineering and Engineering Management, E-ISSN 2157-362X
Keywords
Application study, lean, manufacturing, optimization, simulation, simulation-based optimization
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Production and Automation Engineering; INF201 Virtual Production Development
Identifiers
urn:nbn:se:his:diva-14688 (URN)10.1109/IEEM.2017.8290092 (DOI)000428267800254 ()2-s2.0-85045254668 (Scopus ID)978-1-5386-0948-4 (ISBN)978-1-5386-0947-7 (ISBN)978-1-5386-0949-1 (ISBN)
Conference
2017 International Conference on Industrial Engineering and Engineering Management (IEEM), Singapore, December 10-13, 2017
Available from: 2018-01-25 Created: 2018-01-25 Last updated: 2019-07-02Bibliographically approved
Goienetxea Uriarte, A., Ng, A. H. C., Urenda Moris, M. & Jägstam, M. (2017). Lean, Simulation and Optimization: A maturity model. In: Proceedings of the International Conference on Industrial Engineering and Engineering Management, IEEM2017: . Paper presented at 2017 International Conference on Industrial Engineering and Engineering Management (IEEM), Singapore, December 10-13, 2017 (pp. 1310-1315). IEEE
Open this publication in new window or tab >>Lean, Simulation and Optimization: A maturity model
2017 (English)In: Proceedings of the International Conference on Industrial Engineering and Engineering Management, IEEM2017, IEEE, 2017, p. 1310-1315Conference paper, Published paper (Refereed)
Abstract [en]

This article presents a maturity model that can be applied to support organizations in identifying their current state and guiding their further development with regard to lean, simulation and optimization. The paper identifies and describes different maturity levels and offers guidelines that explain how organizations can grow from lower to higher levels of maturity. In addition, it attempts to provide the starting point for organizations that have applied lean or are willing to implement it and which may also be considering taking decisions in a more efficient way via simulation and optimization.

Place, publisher, year, edition, pages
IEEE, 2017
Series
IEEE International Conference on Industrial Engineering and Engineering Management, E-ISSN 2157-362X
Keywords
Decision-making, lean, maturity model, optimization, organizational performance, simulation
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Production and Automation Engineering; INF201 Virtual Production Development
Identifiers
urn:nbn:se:his:diva-14687 (URN)10.1109/IEEM.2017.8290105 (DOI)000428267800267 ()2-s2.0-85045271642 (Scopus ID)978-1-5386-0948-4 (ISBN)978-1-5386-0947-7 (ISBN)978-1-5386-0949-1 (ISBN)
Conference
2017 International Conference on Industrial Engineering and Engineering Management (IEEM), Singapore, December 10-13, 2017
Available from: 2018-01-25 Created: 2018-01-25 Last updated: 2019-07-02Bibliographically approved
Goienetxea Uriarte, A., Urenda Moris, M., Ng, A. H. C. & Oscarsson, J. (2016). Lean, Simulation and Optimization: A Win-Win combination. In: L. Yilmaz, W. K. V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti (Ed.), Proceedings of the 2015 Winter Simulation Conference: . Paper presented at 2015 Winter Simulation Conference, December 6-9, Huntington Beach, California, USA (pp. 2227-2238). Piscataway, New Jersey: IEEE Computer Society
Open this publication in new window or tab >>Lean, Simulation and Optimization: A Win-Win combination
2016 (English)In: Proceedings of the 2015 Winter Simulation Conference / [ed] L. Yilmaz, W. K. V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, Piscataway, New Jersey: IEEE Computer Society, 2016, p. 2227-2238Conference paper, Published paper (Refereed)
Abstract [en]

Lean and simulation analysis are driven by the same objective, how to better design and improve processes making the companies more competitive. The adoption of lean has been widely spread in companies from public to private sectors and simulation is nowadays becoming more and more popular. Several authors have pointed out the benefits of combining simulation and lean, however, they are still rarely used together in practice. Optimization as an additional technique to this combination is even a more powerful approach especially when designing and improving complex processes with multiple conflicting objectives. This paper presents the mutual benefits that are gained when combining lean, simulation and optimization and how they overcome each other´s limitations. A framework including the three concepts, some of the barriers for its implementation and a real-world industrial example are also described.

Place, publisher, year, edition, pages
Piscataway, New Jersey: IEEE Computer Society, 2016
Series
Proceedings - Winter Simulation Conference, ISSN 0891-7736, E-ISSN 1558-4305 ; 2016
Keywords
Lean, Simulation, Optimization, Decision making
National Category
Production Engineering, Human Work Science and Ergonomics Computer Systems
Research subject
Technology; Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-11766 (URN)10.1109/WSC.2015.7408335 (DOI)000399133902010 ()2-s2.0-84962838930 (Scopus ID)978-1-4673-9743-8 (ISBN)978-1-4673-9741-4 (ISBN)978-1-4673-9742-1 (ISBN)
Conference
2015 Winter Simulation Conference, December 6-9, Huntington Beach, California, USA
Projects
Simulation-based Multi-objective Optimization for Lean production and logistic Networks
Funder
Knowledge Foundation
Available from: 2015-12-17 Created: 2015-12-17 Last updated: 2019-07-02Bibliographically approved
Goienetxea Uriarte, A., Ruiz Zúñiga, E., Urenda Moris, M. & Ng, A. H. C. (2015). System design and improvement of an emergency department using Simulation-Based Multi-Objective Optimization. Paper presented at Mini EURO Conference on Improving Healthcare: new challenges, new approaches, Coimbra, Portugal, 30 March - 1 April 2015. Journal of Physics, Conference Series, 616(1), Article ID 012015.
Open this publication in new window or tab >>System design and improvement of an emergency department using Simulation-Based Multi-Objective Optimization
2015 (English)In: Journal of Physics, Conference Series, ISSN 1742-6588, E-ISSN 1742-6596, Vol. 616, no 1, article id 012015Article in journal (Refereed) Published
Abstract [en]

Discrete Event Simulation (DES) is nowadays widely used to support decision makers in system analysis and improvement. However, the use of simulation for improving stochastic logistic processes is not common among healthcare providers. The process of improving healthcare systems involves the necessity to deal with trade-off optimal solutions that take into consideration a multiple number of variables and objectives. Complementing DES with Multi-Objective Optimization (SMO) creates a superior base for finding these solutions and in consequence, facilitates the decision-making process. This paper presents how SMO has been applied for system improvement analysis in a Swedish Emergency Department (ED). A significant number of input variables, constraints and objectives were considered when defining the optimization problem. As a result of the project, the decision makers were provided with a range of optimal solutions which reduces considerably the length of stay and waiting times for the ED patients. SMO has proved to be an appropriate technique to support healthcare system design and improvement processes. A key factor for the success of this project has been the involvement and engagement of the stakeholders during the whole process.

Place, publisher, year, edition, pages
Institute of Physics Publishing (IOPP), 2015
Keywords
Simulation, Healthcare, Multi-objective Optimization, Discrete Event Simulation, Decision Making, Emergency Department
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Technology; Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-10965 (URN)10.1088/1742-6596/616/1/012015 (DOI)000357994300015 ()2-s2.0-84938118115 (Scopus ID)
Conference
Mini EURO Conference on Improving Healthcare: new challenges, new approaches, Coimbra, Portugal, 30 March - 1 April 2015
Projects
System design and improvement of the emergency department at Skaraborg Hospital in Skövde
Available from: 2015-05-27 Created: 2015-05-27 Last updated: 2018-03-29Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-4604-6429

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