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Urenda Moris, MatíasORCID iD iconorcid.org/0000-0001-5100-4077
Publications (10 of 32) Show all publications
Ruiz Zúñiga, E., García, E. F., Urenda Moris, M., Fathi, M. & Syberfeldt, A. (2021). Holistic simulation-based optimisation methodology for facility layout design with consideration to production and logistics constraints. Proceedings of the Institution of mechanical engineers. Part B, journal of engineering manufacture, 235(14), 2350-2361
Open this publication in new window or tab >>Holistic simulation-based optimisation methodology for facility layout design with consideration to production and logistics constraints
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2021 (English)In: Proceedings of the Institution of mechanical engineers. Part B, journal of engineering manufacture, ISSN 0954-4054, E-ISSN 2041-2975, Vol. 235, no 14, p. 2350-2361Article in journal (Refereed) Published
Abstract [en]

Facility layout design is becoming more challenging as manufacturing moves from traditionally emphasised mass production to mass customisation. The increasing demand for customised products and services is driving the need to increase flexibility and adaptability of both production processes and their material handling systems. A holistic approach for designing facility layouts with optimised flows considering production and logistics systems constraints seems to be missing in the literature. Several tools, including traditional methods, analytic hierarchy process, multiple-attribute decision making, simulation, and optimisation methods, can support such a process. Among these, simulation-based optimisation is the most promising. This paper aims to develop a facility layout design methodology supported by simulation-based optimisation while considering both production and logistics constraints. A literature review of facility layout design with simulation and optimisation and the theoretical and empirical challenges are presented. The integration of simulation-based optimisation in the proposed methodology serves to overcome the identified challenges, providing managers and stakeholders with a decision support system that handles the complex task of facility layout design.

Place, publisher, year, edition, pages
Sage Publications, 2021
Keywords
Simulation-based optimisation, facility layout design, methodology, production, logistics
National Category
Information Systems
Research subject
Production and Automation Engineering; VF-KDO
Identifiers
urn:nbn:se:his:diva-19703 (URN)10.1177/09544054211017310 (DOI)000681100500001 ()2-s2.0-85105954789 (Scopus ID)
Funder
Knowledge Foundation
Note

First Published 10 May 2021

Available from: 2021-05-17 Created: 2021-05-17 Last updated: 2023-11-02Bibliographically approved
Ruiz Zúñiga, E., Urenda Moris, M., Syberfeldt, A., Fathi, M. & Rubio-Romero, J. C. (2020). A Simulation-Based Optimization Methodology for Facility Layout Design in Manufacturing. IEEE Access, 8, 163818-163828
Open this publication in new window or tab >>A Simulation-Based Optimization Methodology for Facility Layout Design in Manufacturing
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2020 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 8, p. 163818-163828Article in journal (Refereed) Published
Abstract [en]

Optimizing production systems is urgent and indispensable if companies are to cope with global competition and a move from mass production to mass customization. The urgency of this need is more obvious in old production plants with a history of modifications, expansions, and adaptations in their production facilities. It is common to find complex, intricate and inefficient systems of material and product flows as a result of poor production facility layout. Several approaches can be used to support the design of optimal facility layouts. However, there is a lack of a suitable generic methodology for designing such layouts. Additionally, there has been little focus on the data and resources required, or on how simulation and optimization can support the design of optimal facilities. To overcome these deficiencies, this paper studies the integration of simulation and optimization for the design and improvement of facility layouts taking into account production and logistics constraints. The paper includes a generic perspective and a detailed implementation. The proposed methodology is evaluated in two case studies and by drawing on the principles and tools of the functional resonance analysis method. This method analyzes the implementation order and variability of a group of processes that can lead to unwanted outcomes. The results can provide managers and other stakeholders with a methodology that adequately considers production and logistics constraints when seeking an optimized facility layout design.

Place, publisher, year, edition, pages
IEEE, 2020
Keywords
Facility Layout Design, Functional Resonance Analysis Method, Production and Logistics Systems, Simulation-Based Optimization.
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-19044 (URN)10.1109/ACCESS.2020.3021753 (DOI)000572966300001 ()2-s2.0-85102893170 (Scopus ID)
Note

CC BY 4.0

Available from: 2020-09-11 Created: 2020-09-11 Last updated: 2023-11-02
Goienetxea, A., Ng, A. H. C. & Urenda Moris, M. (2020). Bringing together Lean and simulation: a comprehensive review. International Journal of Production Research, 58(1), 87-117
Open this publication in new window or tab >>Bringing together Lean and simulation: a comprehensive review
2020 (English)In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 58, no 1, p. 87-117Article, review/survey (Refereed) Published
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, 2020
Keywords
Lean, simulation, review, framework, discrete event simulation, VOSviewer
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering; VF-KDO
Identifiers
urn:nbn:se:his:diva-17493 (URN)10.1080/00207543.2019.1643512 (DOI)000477234000001 ()2-s2.0-85077158606 (Scopus ID)
Funder
Knowledge Foundation
Available from: 2019-08-05 Created: 2019-08-05 Last updated: 2024-01-11Bibliographically approved
Ruiz Zúñiga, E., Flores García, E., Urenda Moris, M. & Syberfeldt, A. (2019). Challenges of Simulation-based Optimization in Facility Layout Design of Production Systems. In: Yan Jin, Mark Price (Ed.), Advances in Manufacturing Technology XXXIII: Proceedings of the 17th International Conference on Manufacturing Research, incorporating the 34th National Conference on Manufacturing Research, September 10–12, 2019, Queen’s University Belfast, UK. Paper presented at 17th International Conference on Manufacturing Research, incorporating the 34th National Conference on Manufacturing Research, September 10–12, 2019, Queen’s University Belfast, UK (pp. 507-512). Amsterdam: IOS Press, 9
Open this publication in new window or tab >>Challenges of Simulation-based Optimization in Facility Layout Design of Production Systems
2019 (English)In: Advances in Manufacturing Technology XXXIII: Proceedings of the 17th International Conference on Manufacturing Research, incorporating the 34th National Conference on Manufacturing Research, September 10–12, 2019, Queen’s University Belfast, UK / [ed] Yan Jin, Mark Price, Amsterdam: IOS Press, 2019, Vol. 9, p. 507-512Conference paper, Published paper (Refereed)
Abstract [en]

Facility layout design (FLD) is becoming more challenging than ever. In particular, modern day manufacturing industry requires advancing from a traditional approach of mass production to one of mass customization including increased flexibility and adaptability. There are several software tools that can support facility layout design among which simulation and optimization are the most powerful – especially when the two techniques are combined into simulation-based optimization (SBO). The aim of this study is to identify the challenges of SBO in FLD of production systems. In doing so, this paper uncovers the challenges of SBO and FLD, which are so far addressed in separate streams of literature. The results of this study present two novel contributions based on two case studies in the Swedish manufacturing industry. First, that challenges of SBO in FLD, previously identified in literature, do not hold equal importance in industrial environments. Our results suggest that challenges in complexity, data noise, and standardization take precedence over challenges of SBO in FLD previously reported in literature. Second, that the origin of challenges of SBO in FLD are not technological in nature, but stem from the increased complexity of factories required in modern day manufacturing companies.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2019
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 9
Keywords
Simulation-based Optimization, Facility Layout Design, Challenges
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
INF201 Virtual Production Development; Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-17707 (URN)10.3233/ATDE190089 (DOI)978-1-64368-008-8 (ISBN)978-1-64368-009-5 (ISBN)
Conference
17th International Conference on Manufacturing Research, incorporating the 34th National Conference on Manufacturing Research, September 10–12, 2019, Queen’s University Belfast, UK
Available from: 2019-09-20 Created: 2019-09-20 Last updated: 2020-12-07Bibliographically 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., 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.

Place, publisher, year, edition, pages
Elsevier, 2018
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)2-s2.0-85061322841 (Scopus ID)
Conference
8th Swedish Production Symposium, SPS 2018, Stockholm, Sweden, May 16-18, 2018
Available from: 2018-07-16 Created: 2018-07-16 Last updated: 2019-11-20Bibliographically approved
Aslam, T., Syberfeldt, A., Ng, A., Pehrsson, L. & Urenda-Moris, M. (2018). Towards an industrial testbed for holistic virtual production development. In: Peter Thorvald, Keith Case (Ed.), Advances in Manufacturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden. Paper presented at 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden (pp. 369-374). Amsterdam: IOS Press
Open this publication in new window or tab >>Towards an industrial testbed for holistic virtual production development
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2018 (English)In: Advances in Manufacturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden / [ed] Peter Thorvald, Keith Case, Amsterdam: IOS Press, 2018, p. 369-374Conference paper, Published paper (Refereed)
Abstract [en]

Virtual production development is adopted by many companies in the production industry and digital models and virtual tools are utilized for strategic, tactical and operational decisions in almost every stage of the value chain. This paper suggest a testbed concept that aims the production industry to adopt a virtual production development process with integrated tool chains that enables holistic optimizations, all the way from the overall supply chain performance down to individual equipment/devices. The testbed, which is fully virtual, provides a mean for development and testing of integrated digital models and virtual tools, including both technical and methodological aspects.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2018
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 8
Keywords
Virtual production development, testbed, integrated tool chains, simulation, optimization
National Category
Other Engineering and Technologies not elsewhere specified
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-16375 (URN)10.3233/978-1-61499-902-7-369 (DOI)000462212700059 ()2-s2.0-85057415907 (Scopus ID)978-1-61499-901-0 (ISBN)978-1-61499-902-7 (ISBN)
Conference
16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden
Available from: 2018-11-08 Created: 2018-11-08 Last updated: 2019-04-08Bibliographically 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: 2020-12-07Bibliographically approved
Ruiz Zúñiga, E., Urenda Moris, M. & Syberfeldt, A. (2017). Integrating Simulation-Based Optimization, Lean, and the Concepts of Industry 4.0. In: W. K. V. Chan, A. D'Ambrogio, G. Zacharewicz, N. Mustafee, G. Wainer, E. Page (Ed.), Proceedings of the 2017 Winter Simulation Conference: . Paper presented at Winter Simulation Conference, Las Vegas, December 3-6, 2017 (pp. 3828-3839). IEEE
Open this publication in new window or tab >>Integrating Simulation-Based Optimization, Lean, and the Concepts of Industry 4.0
2017 (English)In: Proceedings of the 2017 Winter Simulation Conference / [ed] W. K. V. Chan, A. D'Ambrogio, G. Zacharewicz, N. Mustafee, G. Wainer, E. Page, IEEE, 2017, p. 3828-3839Conference paper, Published paper (Refereed)
Abstract [en]

Nowadays, due to the need of innovation and adaptation for the mass production of customized goods,many industries are struggling to compete with the manufacturing sector emerging in different countriesaround the world. The understanding and implementation of different improvement techniques isnecessary in order to take part in the so-called fourth industrial revolution, Industry 4.0. This paperinvestigates how two well-known improvement approaches, namely lean and simulation-basedoptimization, can be combined with the concepts of Industry 4.0 to improve efficiency and avoid movingproduction to other countries. Going through an industrial case study, the paper discusses how such acombination could be carried out and how the different strengths of the three approaches can be utilizedtogether. The case study focuses on how the efficiency of a production site can be increased and howIndustry 4.0 can support the improvement of the internal logistics on the shop floor.

Place, publisher, year, edition, pages
IEEE, 2017
Series
Winter Simulation Conference. Proceedings, E-ISSN 1558-4305 ; 2017
Keywords
Simulation-based Optimization, Lean Manufacturing, Industry 4.0, Production, Internal Logistics, Shop floor
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering Transport Systems and Logistics
Research subject
Production and Automation Engineering; INF201 Virtual Production Development
Identifiers
urn:nbn:se:his:diva-14644 (URN)10.1109/WSC.2017.8248094 (DOI)000427768604004 ()2-s2.0-85044501080 (Scopus ID)978-1-5386-3428-8 (ISBN)978-1-5386-3429-5 (ISBN)978-1-5386-3430-1 (ISBN)
Conference
Winter Simulation Conference, Las Vegas, December 3-6, 2017
Funder
Knowledge Foundation
Available from: 2018-01-09 Created: 2018-01-09 Last updated: 2020-12-07Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-5100-4077

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