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Ruiz Zúñiga, EnriqueORCID iD iconorcid.org/0000-0003-4180-6003
Publications (10 of 12) Show all publications
Nourmohammadi, A., Fathi, M., Ruiz Zúñiga, E. & Ng, A. H. C. (2019). A Genetic Algorithm for Bi-Objective Assembly Line Balancing Problem. 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. 519-524). Amsterdam: IOS Press, 9
Open this publication in new window or tab >>A Genetic Algorithm for Bi-Objective Assembly Line Balancing Problem
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. 519-524Conference paper, Published paper (Refereed)
Abstract [en]

Assembly line designs in manufacturing commonly face the key problem of dividing the assembly tasks among the working stations so that the efficiency of the line is optimized. This problem is known as the assembly line balancing problem which is known to be NP-hard. This study, proposes a bi-objective genetic algorithm to cope with the assembly line balancing problem where the considered objectives are the utilization of the assembly line and the workload smoothness measured as the line efficiency and the variation of workload, respectively. The performance of the proposed genetic algorithm is tested through solving a set of standard problems existing in the literature. The computational results show that the genetic algorithm is promising in providing good solutions to the assembly line balancing problem.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2019
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 9
Keywords
Assembly line balancing, bi-objectives, Genetic Algorithm
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-17679 (URN)10.3233/ATDE190091 (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
Projects
This study is supported by the European Union’s Horizon 2020 research and innovation program under grant agreement no. 723711 through the MANUWORK project.
Funder
EU, Horizon 2020, 723711
Available from: 2019-09-13 Created: 2019-09-13 Last updated: 2019-09-16Bibliographically 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: 2019-09-26Bibliographically approved
Flores Garcia, E., Ruiz Zúñiga, E., Bruch, J., Urenda Moris, M. & Syberfeldt, A. (2018). Simulation-based Optimization for Facility Layout Design in Conditions of High Uncertainty. Paper presented at 51st CIRP Conference on Manufacturing Systems, Stockholm, May 16-18, 2018. Procedia CIRP, 72, 334-339
Open this publication in new window or tab >>Simulation-based Optimization for Facility Layout Design in Conditions of High Uncertainty
Show others...
2018 (English)In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 334-339Article in journal (Refereed) Published
Abstract [en]

Despite the increased use of Simulation based Optimization, the design of facility layout is challenged by high levels of uncertainty associatedwith new production processes. Addressing this issue, this paper aims to understand the conceptual modeling activities of Simulation-basedOptimization for facility layout design in conditions of high uncertainty. Based on three in-depth case studies, the results of this paper showhow characterization criteria of production systems can be used in conceptual modelling to reduce uncertainty. These results may be essentialto support managers and stakeholders during the introduction of new production processes in the design of facility layouts.

Place, publisher, year, edition, pages
Elsevier, 2018
Keywords
uncertainty reduction, simulation based optimization, facility layout, decision support, production system design
National Category
Other Engineering and Technologies not elsewhere specified
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-15189 (URN)10.1016/j.procir.2018.03.227 (DOI)2-s2.0-85049552085 (Scopus ID)
Conference
51st CIRP Conference on Manufacturing Systems, Stockholm, May 16-18, 2018
Funder
Knowledge Foundation
Available from: 2018-05-30 Created: 2018-05-30 Last updated: 2018-10-31Bibliographically 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
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: 2019-01-24Bibliographically approved
Ruiz Zúñiga, E., Syberfeldt, A. & Urenda Moris, M. (2017). The Internet of Things, Factory of Things and Industry 4.0 in Manufacturing: Current and Future Implementations. In: James Gao, Mohammed El Souri, Simeon Keates (Ed.), Advances in Manufacturing Technology XXXI: Proceedings of the 15th International Conference on Manufacturing Research, Incorporating the 32nd National Conference on Manufacturing Research, September 5–7, 2017, University of Greenwich, UK. Paper presented at 15th International Conference on Manufacturing Research ICMR 2017. Incorporating the 32nd National Conference on Manufacturing Research. University of Greenwich, London, September 5-7, 2017 (pp. 221-226). IOS Press
Open this publication in new window or tab >>The Internet of Things, Factory of Things and Industry 4.0 in Manufacturing: Current and Future Implementations
2017 (English)In: Advances in Manufacturing Technology XXXI: Proceedings of the 15th International Conference on Manufacturing Research, Incorporating the 32nd National Conference on Manufacturing Research, September 5–7, 2017, University of Greenwich, UK / [ed] James Gao, Mohammed El Souri, Simeon Keates, IOS Press, 2017, p. 221-226Conference paper, Published paper (Refereed)
Abstract [en]

In the currently rapidly changing industrialized world, globalization,product customization and automation are playing an imposing role in thedevelopment of the manufacturing sector. Nowadays, the innovative concepts ofThe Internet of Things, Factory of Things and Industry 4.0 are aimed torevolutionize the way technology can help improve production around the world.While in some international corporations these concepts are being deeply studiedand are starting to be implemented, also in middle-size and large manufacturers itis clear they could contribute with many advantages; however, skepticism anduncertainty are still present among managers and stakeholders. In this paper, thecurrent and coming state-of-the-art technology and implementation of the Factoryof Things paradigm are presented and examples of the current implementation inglobal manufacturing companies are analyzed. Additionally, this article willdiscuss the potential implementation of this Industry 4.0 in a large manufacturer,and how it can help increase the control and efficiency of production, materialflows, internal logistics and production planning.

Place, publisher, year, edition, pages
IOS Press, 2017
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 6
Keywords
The Internet of Things, Factory of Things, Smart Factory, Industry 4.0, manufacturing, internal logistics, production
National Category
Control Engineering Other Engineering and Technologies not elsewhere specified
Research subject
Production and Automation Engineering; INF201 Virtual Production Development
Identifiers
urn:nbn:se:his:diva-14202 (URN)10.3233/978-1-61499-792-4-221 (DOI)000440620700035 ()2-s2.0-85028371657 (Scopus ID)978-1-61499-791-7 (ISBN)978-1-61499-792-4 (ISBN)
Conference
15th International Conference on Manufacturing Research ICMR 2017. Incorporating the 32nd National Conference on Manufacturing Research. University of Greenwich, London, September 5-7, 2017
Funder
Knowledge Foundation
Available from: 2017-10-05 Created: 2017-10-05 Last updated: 2019-01-24Bibliographically approved
Ruiz Zúñiga, E. (2016). A simulation-based approach for optimization of production logistics with consideration to production layout: Research Proposal.
Open this publication in new window or tab >>A simulation-based approach for optimization of production logistics with consideration to production layout: Research Proposal
2016 (English)Report (Other academic)
Abstract [en]

Manufacturing sectors in Sweden have a long tradition and represent a significant share of the national gross domestic product and the export values. Most of the Swedish manufacturing companies have gone through a modernization and adaptation process in order to be able to compete on a globalized market. Many plants, however, still have non-optimized shop floors as a consequence of adaptations over time without redesigning its production and logistics flows and with a lack of an overall strategy. To support the optimization of shop floors, this project suggests the combined use of Discrete-Event Simulation (DES) and Simulation-Based Multi-objective Optimization (SBO) under the umbrella of a design and creation research strategy. The aim of the project is to support the improvement and optimization of high product mix and a low-volume of customized products manufacturing systems by considering production and logistics flows along with the shop floor layout. The methodology is intended to contribute to significantly increase the productivity and efficiency of the Swedish manufacturing industry and help companies to survive on the globalized market. The potential results can serve for decision makers and stakeholders to apply changes and adaptations in the system considering the mid and long term goals of the company. Going through different case studies implemented in a middle-size water pumps manufacturer, this methodology will be useful in practice and it will provide a decision support system for this specific industrial partner and will serve as a guideline for other manufacturing companies.

Publisher
p. 14
Keywords
simulation-based optimization, mix-model production, logistics, layout
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-13197 (URN)
Funder
Knowledge Foundation
Note

Research proposal, PhD programme, University of Skövde

Available from: 2016-12-06 Created: 2016-12-06 Last updated: 2018-03-28Bibliographically approved
Ruiz Zúñiga, E., Urenda Moris, M. & Syberfeldt, A. (2016). A simulation-based multi-objective optimization approach for production and logistics considering the production layout. In: Proceedings of the 7th Swedish Production Symposium: . Paper presented at 7th Swedish Production Symposium, Lund, Sweden, October 25-27, 2016.
Open this publication in new window or tab >>A simulation-based multi-objective optimization approach for production and logistics considering the production layout
2016 (English)In: Proceedings of the 7th Swedish Production Symposium, 2016Conference paper, Published paper (Refereed)
Abstract [en]

Manufacturing sectors in Sweden have a long tradition and represent a significant share of the national gross domestic product and the export values. Most of the Swedish manufacturing companies have gone through a modernization and adaptation process in order to be able to compete on a globalized market. Many plants, however, still have non-optimized shop floors as a consequence of the shop floors being adapted over time without redesigning its production and logistics flows and with a lack of an overall strategy. To support the optimization of shop floors, this paper suggests the combined use of Discrete-Event Simulation and Simulation-Based Multi-objective Optimization. The aim of the paper is to analyze a simulation methodology that supports the optimization of shop floors by considering production and logistics flows along with the shop floor layout. The methodology is intended to contribute to significantly increase the productivity and efficiency of the Swedish manufacturing industry and help companies to survive on the globalized market. Through a case study, the paper shows that the proposed methodology is useful in practice and that it provides a decision support system for manufacturing companies.

Keywords
Simulation-based optimization, mix-model production, logistics, layout
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering Other Engineering and Technologies not elsewhere specified
Research subject
Technology; Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-13085 (URN)
Conference
7th Swedish Production Symposium, Lund, Sweden, October 25-27, 2016
Funder
Knowledge Foundation
Available from: 2016-11-09 Created: 2016-11-09 Last updated: 2018-03-28Bibliographically approved
Ruiz Zúñiga, E., Urenda Moris, M. & Syberfeldt, A. (2016). Production Logistics Design and Development Support: A Simulation-Based Optimization Case Study (WIP). In: Society for Modeling & Simulation International (SCS) (Ed.), SummerSim'16, 2016 July 24-27, Palais des congres de Montreal (Montreal Convention Center) | Montreal, Quebec, Canada: . Paper presented at 48th Summer Computer Simulation Conference, SCSC 2016, Part of the 2016 Summer Simulation Multi-Conference, SummerSim 2016, July 24-27, Montreal, Quebec, Canada (pp. 56:1-56:6). The Society for Modeling and Simulation International, Article ID 56.
Open this publication in new window or tab >>Production Logistics Design and Development Support: A Simulation-Based Optimization Case Study (WIP)
2016 (English)In: SummerSim'16, 2016 July 24-27, Palais des congres de Montreal (Montreal Convention Center) | Montreal, Quebec, Canada / [ed] Society for Modeling & Simulation International (SCS), The Society for Modeling and Simulation International, 2016, p. 56:1-56:6, article id 56Conference paper, Published paper (Refereed)
Abstract [en]

Manufacturing sectors in Sweden have a long history that leads to common non-optimized flows on the shop floor. Especially when having a really high product mix and a low-volume of customized products, a great deal of effort with respect to flow optimization is needed to stay present and compete in the globalized market. The goal of this project is to support the design and development of the implementation of new production systems and logistics flows considering the shop floor plant layout of a Swedish middle-size water pumps factory. In this paper, with the help of different types of simulation models and optimization, some results of a new technologically adapted production line are analyzed and relevant information and potential improvements in the production are found. The further development of optimization studies using the exiting simulation models is stated as ongoing and future work. The obtained and potential results can serve for decision makers and stakeholders to apply changes and adaptations in the system considering the mid and long term goals of the company.

Place, publisher, year, edition, pages
The Society for Modeling and Simulation International, 2016
Series
Simulation Series, ISSN 0735-9276 ; Vol 48 iss 9
Keywords
Simulation-based optimization, mix-model assembly line, production, logistics, layout
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering Other Engineering and Technologies not elsewhere specified
Research subject
Technology; Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-12734 (URN)10.22360/SummerSim.2016.SCSC.066 (DOI)2-s2.0-84994593680 (Scopus ID)978-1-5108-2424-9 (ISBN)
Conference
48th Summer Computer Simulation Conference, SCSC 2016, Part of the 2016 Summer Simulation Multi-Conference, SummerSim 2016, July 24-27, Montreal, Quebec, Canada
Funder
Knowledge Foundation
Available from: 2016-08-02 Created: 2016-08-02 Last updated: 2018-06-28Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-4180-6003

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