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Publications (10 of 98) Show all publications
Iriondo Pascual, A., Högberg, D., Syberfeldt, A., Brolin, E. & Hanson, L. (2020). Application of Multi-objective Optimization on Ergonomics in Production: A Case Study. In: Massimo Di Nicolantonio, Emilio Rossi, Thomas Alexander (Ed.), Advances in Additive Manufacturing, Modeling Systems and 3D Prototyping: Proceedings of the AHFE 2019 International Conference on Additive Manufacturing, Modeling Systems and 3D Prototyping, July 24-28, 2019, Washington D.C., USA. Paper presented at International Conference on Applied Human Factors and Ergonomics (AHFE), Washington D.C, USA, July 24-28, 2019 (pp. 584-594). Springer
Open this publication in new window or tab >>Application of Multi-objective Optimization on Ergonomics in Production: A Case Study
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2020 (English)In: Advances in Additive Manufacturing, Modeling Systems and 3D Prototyping: Proceedings of the AHFE 2019 International Conference on Additive Manufacturing, Modeling Systems and 3D Prototyping, July 24-28, 2019, Washington D.C., USA / [ed] Massimo Di Nicolantonio, Emilio Rossi, Thomas Alexander, Springer, 2020, p. 584-594Conference paper, Published paper (Refereed)
Abstract [en]

Taking a holistic perspective is central in production development, aiming to optimize ergonomics and overall production system performance. Hence, there is a need for tools and methods that can support production companies to identify the production system alternatives that are optimal regarding both ergonomics and production efficiency. The paper presents a devised case study where multi-objective optimization is applied, as a step to towards the development of such an optimization tool. The overall objective in the case study is to find the best order in which an operator performs manual tasks during a workday, considering ergonomics and production system efficiency simultaneously. More specifically, reducing the risk of injury from lifting tasks and improving the throughput are selected as the two optimization objectives. An optimization tool is developed, which communicates with a digital human modelling tool to simulate work tasks and assess ergonomics. 

Place, publisher, year, edition, pages
Springer, 2020
Series
Advances in Intelligent Systems and Computing, ISSN 2194-5357, E-ISSN 2194-5365 ; 975
Keywords
Digital human modelling, Ergonomics, Optimization, Productivity, Simulation, 3D modeling, Additives, Efficiency, Manufacture, Holistic perspectives, Optimization tools, Production companies, Production development, Production efficiency, Tools and methods, Multiobjective optimization
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-17417 (URN)10.1007/978-3-030-20216-3_54 (DOI)2-s2.0-85067415239 (Scopus ID)978-3-030-20215-6 (ISBN)978-3-030-20216-3 (ISBN)
Conference
International Conference on Applied Human Factors and Ergonomics (AHFE), Washington D.C, USA, July 24-28, 2019
Available from: 2019-07-09 Created: 2019-07-09 Last updated: 2019-08-06Bibliographically approved
Fathi, M., Nourmohammadi, A., Ng, A. H. C., Syberfeldt, A. & Eskandari, H. (2019). An improved genetic algorithm with variable neighborhood search to solve the assembly line balancing problem. Engineering computations
Open this publication in new window or tab >>An improved genetic algorithm with variable neighborhood search to solve the assembly line balancing problem
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2019 (English)In: Engineering computations, ISSN 0264-4401, E-ISSN 1758-7077Article in journal (Refereed) Epub ahead of print
Abstract [en]
  • Purpose – This study aims to propose an efficient optimization algorithm to solve the assembly line balancing problem (ALBP). The ALBP arises in high-volume, lean production systems when decision makers aim to design an efficient assembly line while satisfying a set of constraints.
  • Design/methodology/approach – An improved genetic algorithm (IGA) is proposed in this study to deal with ALBP in order to optimize the number of stations and the workload smoothness.
  • Findings – To evaluate the performance of the IGA, it is used to solve a set of well-known benchmark problems and a real-life problem faced by an automobile manufacturer. The solutions obtained are compared against two existing algorithms in the literature and the basic genetic algorithm. The comparisons show the high efficiency and effectiveness of the IGA in dealing with ALBPs.
  • Originality/value – The proposed IGA benefits from a novel generation transfer mechanism that improves the diversification capability of the algorithm by allowing population transfer between different generations. In addition, an effective variable neighborhood search is employed in the IGA to enhance its local search capability.
Place, publisher, year, edition, pages
Emerald Group Publishing Limited, 2019
Keywords
assembly line balancing, genetic algorithm, variable neighborhood search, generation transfer
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-17157 (URN)10.1108/EC-02-2019-0053 (DOI)2-s2.0-85071617279 (Scopus ID)
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: 2019-06-18 Created: 2019-06-18 Last updated: 2019-09-24Bibliographically approved
Fathi, M., Ghobakhloo, M. & Syberfeldt, A. (2019). An Interpretive Structural Modeling of Teamwork Training in Higher Education. Education Sciences, 9(1), 1-20
Open this publication in new window or tab >>An Interpretive Structural Modeling of Teamwork Training in Higher Education
2019 (English)In: Education Sciences, E-ISSN 2227-7102, Vol. 9, no 1, p. 1-20Article in journal (Refereed) Published
Abstract [en]

In the past decade, the importance of teamwork training in higher education and employers’ enthusiasm for recruiting team players have been widely discussed in the literature. Yet, the process through which effective teamwork training is developed in a higher education setting has not yet been properly discussed. The present study aims to map the precedence relationships among the key determinants of teamwork training effectiveness and explain the process through which an effective teamwork training program can be developed. The study first conducted an extensive review of the literature to highlight the key determinants of effective teamwork training. Next, the study benefitted from an interpretive structural modeling technique and captured the opinions of a group of teamwork training experts to further map the interrelationships among the potential determinants that were identified. By listing the key determinants of effective teamwork training, mapping their interrelationships, and identifying their driving and dependence power, the present study is expected to help practitioners and academicians through providing a detailed understanding of the process through which an effective teamwork training program can be developed in a higher education context.

Place, publisher, year, edition, pages
Switzerland: MDPI, 2019
Keywords
teamwork, higher education, determinants, interpretive structural modeling
National Category
Pedagogy
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-16568 (URN)10.3390/educsci9010016 (DOI)000464170900001 ()2-s2.0-85061216921 (Scopus ID)
Available from: 2019-01-16 Created: 2019-01-16 Last updated: 2019-05-09Bibliographically approved
Fathi, M., Nourmohammadi, A., Ng, A. H. C. & Syberfeldt, A. (2019). An optimization model for balancing assembly lines with stochastic task times and zoning constraints. IEEE Access, 7, 32537-32550, Article ID 8663269.
Open this publication in new window or tab >>An optimization model for balancing assembly lines with stochastic task times and zoning constraints
2019 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 32537-32550, article id 8663269Article in journal (Refereed) Published
Abstract [en]

This study aims to bridge the gap between theory and practice by addressing a real-world assembly line balancing problem (ALBP) where task times are stochastic and there are zoning constraints in addition to the commonly known ALBP constraints. A mixed integer programming (MIP) model is proposed for each of the straight and U-shaped assembly line configurations. The primary objective in both cases is to minimize the number of stations; minimizing the maximum of stations’ mean time and the stations’ time variance are considered secondary objectives. Four different scenarios are discussed for each model, with differences in the objective function. The models are validated by solving a real case taken from an automobile manufacturing company and some standard test problems available in the literature. The results indicate that both models are able to provide optimum solutions for problems of different sizes. The technique for order preference by similarity to ideal solution (TOPSIS) is used to create reliable comparisons of the different scenarios and valid analysis of the results. Finally, some insights regarding the selection of straight and U-shaped layouts are provided.

Place, publisher, year, edition, pages
IEEE, 2019
Keywords
assembly line balancing, mathematical programming, stochastic, zoning constraints
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-16689 (URN)10.1109/ACCESS.2019.2903738 (DOI)000463040400001 ()2-s2.0-85063577558 (Scopus ID)
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: 2019-03-09 Created: 2019-03-09 Last updated: 2019-05-09Bibliographically 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
Strand, M. & Syberfeldt, A. (2019). Incorporating external data into a BI solution at a public waste management organization. International Journal of Business Intelligence Research, 10(2), 36-56
Open this publication in new window or tab >>Incorporating external data into a BI solution at a public waste management organization
2019 (English)In: International Journal of Business Intelligence Research, ISSN 1947-3591, E-ISSN 1947-3605, Vol. 10, no 2, p. 36-56Article in journal (Refereed) Published
Abstract [en]

Organizations are showing an increasing interest in incorporating external data into their business intelligence solutions. Such data allows for advanced analytics and enables more comprehensive and inclusive decision-making. However, external data incorporation is relatively unexplored in the literature, and scientifically published details on up-and-running BI solutions are very sparse. In addition, published literature concerning the incorporation of external data into BI solutions is often rather synoptic or rather old (originating from data warehouse related literature). Therefore, the authors present the results of an action case study at a public waste management organization, illustrating detailed aspects of external data incorporation related to the back-end of the solution such as data selection, source characteristics, acquisition technologies and frequencies, and integration approaches. Given that the external origin of the data poses specific problems that must be overcome in order to allow for successful incorporation initiatives, special attention was paid to such problems. Copyright © 2019, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

Keywords
Business Intelligence, Case Study, External Data, Waste Management
National Category
Other Computer and Information Science Media Engineering Information Systems
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-17479 (URN)10.4018/IJBIR.2019070104 (DOI)2-s2.0-85068688761 (Scopus ID)
Note

EISBN13: 9781522566939

Available from: 2019-07-25 Created: 2019-07-25 Last updated: 2019-08-06Bibliographically approved
Land, N., Syberfeldt, A., Torgny, A. & Vallhagen, J. (2019). Virtual Human-Robot Collaboration: The Industry's Perspective on Potential Applications and Benefits. 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. 161-166). Amsterdam: IOS Press, 9
Open this publication in new window or tab >>Virtual Human-Robot Collaboration: The Industry's Perspective on Potential Applications and Benefits
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. 161-166Conference paper, Published paper (Refereed)
Abstract [en]

Two keystones of Industry 4.0 are the increased use of autonomous robots and advanced simulation software. Human-Robot Collaboration (HRC) combines the strengths of humans and robots, opening up application areas that previously could not be automated. However, the realization of HRC on industrial shop floors is held back by several challenges: safety, trust, the need for intuitive interfaces, and design methods. This study investigates the automotive industry’s perspective on relevant application areas and potential benefits of HRC. The data were collected through a survey of 185 participants from a variety of working roles in the automotive industry. The results of the study indicate that participants from the automotive industry consider that the areas best suited to the implementation of collaborative robots are material handling, assembly, and quality control, with potential benefits in ergonomics, efficiency, and quality. The results can be used for the development of a future virtual HRC simulation model.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2019
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 9
Keywords
Human-Robot Collaboration, Virtual Simulation
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
VF-KDO; Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-17704 (URN)10.3233/ATDE190029 (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: 2019-09-19 Created: 2019-09-19 Last updated: 2019-09-24Bibliographically approved
Syberfeldt, A., Ayani, M. & Holm, M. (2018). A holistic solution for integrating a simulated twin of an automation system during the system’s entire life-cycle. 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. 405-410). Amsterdam: IOS Press
Open this publication in new window or tab >>A holistic solution for integrating a simulated twin of an automation system during the system’s entire life-cycle
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. 405-410Conference paper, Published paper (Refereed)
Abstract [en]

This paper describes a project that attempts to develop a holistic solution for integrating a simulated twin of an automation system during the system’s entire life-cycle. With such holistic solution, virtual commission could be undertaken in all steps of the life-cycle which facilitates companies in realizing flexible and intelligent automation systems. Based on the simulated twin, the companies could easily and cost-efficiently evaluate modifications, make improvements, and train operators when changes in the production setup occurs due mass-customization or new products being introduced. This aids the companies in staying competitive on a global and rapidly changing market and meet the challenges coming with the forth industrial revolution, such as mass-customization and short product life-cycles.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2018
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 8
Keywords
Simulated twin, Virtual commissioning, Automation system
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
INF201 Virtual Production Development; Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-16374 (URN)10.3233/978-1-61499-902-7-405 (DOI)000462212700065 ()2-s2.0-85057394455 (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
Gustavsson, P. & Syberfeldt, A. (2018). A New Algorithm Using the Non-dominated Tree to improve Non-dominated Sorting. Evolutionary Computation, 26(1), 89-116
Open this publication in new window or tab >>A New Algorithm Using the Non-dominated Tree to improve Non-dominated Sorting
2018 (English)In: Evolutionary Computation, ISSN 1063-6560, E-ISSN 1530-9304, Vol. 26, no 1, p. 89-116Article in journal (Refereed) Published
Abstract [en]

Non-dominated sorting is a technique often used in evolutionary algorithms to determine the quality of solutions in a population. The most common algorithm is the Fast Non-dominated Sort (FNS). This algorithm, however, has the drawback that its performance deteriorates when the population size grows. The same drawback applies also to other non-dominating sorting algorithms such as the Efficient Non-dominated Sort with Binary Strategy (ENS-BS). An algorithm suggested to overcome this drawback is the Divide-and-Conquer Non-dominated Sort (DCNS) which works well on a limited number of objectives but deteriorates when the number of objectives grows. This paper presents a new, more efficient, algorithm called the Efficient Non-dominated Sort with Non-Dominated Tree (ENS-NDT). ENS-NDT is an extension of the ENS-BS algorithm and uses a novel Non-Dominated Tree (NDTree) to speed up the non-dominated sorting. ENS-NDT is able to handle large population sizes and a large number of objectives more efficiently than existing algorithms for non-dominated sorting. In the paper, it is shown that with ENS-NDT the runtime of multi-objective optimization algorithms such as the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) can be substantially reduced.

Place, publisher, year, edition, pages
MIT Press, 2018
National Category
Other Engineering and Technologies not elsewhere specified
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-13336 (URN)10.1162/EVCO_a_00204 (DOI)000426562300004 ()2-s2.0-85042773821 (Scopus ID)
Available from: 2017-01-25 Created: 2017-01-25 Last updated: 2018-03-20Bibliographically approved
Liu, Y., Syberfeldt, A. & Strand, M. (2018). A Review of Simulation Based Life Cycle Assessment in Manufacturing Industry. 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, Skövde, Sweden. Paper presented at 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11 – 13, 2018, Skövde, Sweden (pp. 381-386). Amsterdam, Berlin, Washington,DC: IOS Press, 8
Open this publication in new window or tab >>A Review of Simulation Based Life Cycle Assessment in Manufacturing Industry
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, Skövde, Sweden / [ed] Peter Thorvald, Keith Case, Amsterdam, Berlin, Washington,DC: IOS Press, 2018, Vol. 8, p. 381-386Conference paper, Published paper (Refereed)
Abstract [en]

The manufacturing industry has a duty to minimize their environmental impact and more and more legislations include environmental impact evaluations from a life cycle perspective to avoid burden shift. Current manufacturing industry increase their use of computer-based simulations for optimizing production processes. In recent years, a number of studies have been published, combining simulations with life cycle assessments (LCA), to evaluate and minimize the environmental impact of production activities, as part of improving the production processes. Still, current knowledge concerning simulations for LCA is rather scattered. Therefore, this paper reviews relevant literature covering simulation based LCA for production development. The results of the review and cross comparison of papers are structured following the 6 categories in line with the ISO standard definition of LCA (goal formulation, scope definition, environmental impact assessment, data quality, level of modelling details, and model validation) and report the strengths and constraints of the reviewed studies. 

Place, publisher, year, edition, pages
Amsterdam, Berlin, Washington,DC: IOS Press, 2018
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 8
Keywords
life cycle assessment, production process, simulation
National Category
Engineering and Technology Production Engineering, Human Work Science and Ergonomics Environmental Analysis and Construction Information Technology
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-16342 (URN)10.3233/978-1-61499-902-7-381 (DOI)000462212700061 ()2-s2.0-85057394386 (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, Skövde, Sweden
Available from: 2018-10-26 Created: 2018-10-26 Last updated: 2019-04-05Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-3973-3394

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