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Fathi, M., Nourmohammadi, A., Ng, A. H. C., Syberfeldt, A. & Eskandari, H. (2020). An improved genetic algorithm with variable neighborhood search to solve the assembly line balancing problem. Engineering computations, 37(2), 501-521
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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2020 (English)In: Engineering computations, ISSN 0264-4401, E-ISSN 1758-7077, Vol. 37, no 2, p. 501-521Article in journal (Refereed) Published
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, 2020
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)000525097800002 ()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: 2020-04-30Bibliographically approved
Syberfeldt, A. & Smedberg, H. (2020). Ant colony optimisation for solving real-world pickup and delivery problems with hard time windows. World Review of Intermodal Transportation Research (WRITR), 9(1), 76-96
Open this publication in new window or tab >>Ant colony optimisation for solving real-world pickup and delivery problems with hard time windows
2020 (English)In: World Review of Intermodal Transportation Research (WRITR), ISSN 1749-4729, E-ISSN 1749-4737, Vol. 9, no 1, p. 76-96Article in journal (Refereed) Published
Abstract [en]

This paper compares the performance of the classic genetic algorithm with the more recently proposed ant colony optimisation for solving real-world pickup and delivery problems with hard time windows. A real-world problem that is present worldwide – waste collection – is used to evaluate the algorithms. As in most real-world waste collection problems, many of the waste bins have time windows. The time windows stem from such things as safety regulations and customer agreements, and must be strictly adhered to. The optimisation showed that the genetic algorithm is better than the ant colony optimisation when utilising standard implementations of both algorithms. However, when the algorithms are enhanced with a local search procedure, the ant colony optimisation immediately becomes superior and achieves improved results. Local search seems to be a drawback for the genetic algorithm when hard time windows are involved. Various implementations of the local search procedure are evaluated in this paper using five different test sets. Recommendations for future implementations are given as well as additional enhancements which could improve the performance of the ant colony optimisation. 

Place, publisher, year, edition, pages
InderScience Publishers, 2020
Keywords
Ant colony optimisation, Hard time windows, Pickup and delivery problem
National Category
Production Engineering, Human Work Science and Ergonomics Robotics
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-18414 (URN)10.1504/WRITR.2020.106451 (DOI)2-s2.0-85083334573 (Scopus ID)
Available from: 2020-04-30 Created: 2020-04-30 Last updated: 2020-05-04Bibliographically approved
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
Nikolakis, N., Senington, R., Sipsas, K., Syberfeldt, A. & Makris, S. (2020). On a containerized approach for the dynamic planning and control of a cyber - physical production system. Robotics and Computer-Integrated Manufacturing, 64, Article ID 101919.
Open this publication in new window or tab >>On a containerized approach for the dynamic planning and control of a cyber - physical production system
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2020 (English)In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 64, article id 101919Article in journal (Refereed) Published
Abstract [en]

The increased complexity of modern production systems requires sophisticated system control approaches to maintain high levels of flexibility. Furthermore, the request for customized production with the introduction of heterogeneous production resources, increases the diversity of manufacturing systems making their reconfiguration complex and time consuming. In this paper, an end-to-end approach for reconfigurable cyber-physical production systems is discussed, enabled by container technologies. The presented approach enhances flexibility in a cyber-physical production system (CPPS) through the dynamic reconfiguration of the automation system and the production schedule, based on occurring events. High-level management of manufacturing operations is performed on a centralized node while the data processing and execution control is handled at the network edge. Runtime events are generated at the edge and in smart connected devices via means of a variant of IEC61499 function blocks. Software containers manage the deployment and low-level orchestration of FBs at the edge devices. All aspects of the proposed solution have been implemented on a software framework and applied in a small scale CPPS coming from the automotive industry.

Keywords
Cyber-physical production system, Planning, Reconfiguration, Containerization
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-18283 (URN)10.1016/j.rcim.2019.101919 (DOI)2-s2.0-85077509574 (Scopus ID)
Available from: 2020-03-04 Created: 2020-03-04 Last updated: 2020-04-22Bibliographically approved
Strand, M. & Syberfeldt, A. (2020). Using external data in a BI solution to optimise waste management. Journal of Decision Systems, 29(1), 53-68
Open this publication in new window or tab >>Using external data in a BI solution to optimise waste management
2020 (English)In: Journal of Decision Systems, ISSN 1246-0125, E-ISSN 2116-7052, Vol. 29, no 1, p. 53-68Article in journal (Refereed) Published
Abstract [en]

BI solutions are constantly being developed to support decision-making at various organisational levels. These solutions facilitate the compilation, aggregation and summarisation of large volumes of data. Consequently, the business value created by these systems is increasing as they sustain more and more advanced analytics, ranging from descriptive analytics, to predictive analytics, to prescriptive analytics. However, most organisations work primarily with internal data. Despite many references in the literature to the value hidden in external data, details on how such data can be used are scarce. In this paper, we present the results of an extensive action case study at a public waste management company. The results illustrate how external data from several external data sources, integrated into an up-and-running BI solution, are used jointly to allow for descriptive and predictive analytics, as well as prescriptive analytics. In addition, details of these analytical values are given and related to organisational benefits.

Place, publisher, year, edition, pages
Taylor & Francis Group, 2020
Keywords
Business intelligence, external data, decision-support system, waste management
National Category
Production Engineering, Human Work Science and Ergonomics Information Systems
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-18334 (URN)10.1080/12460125.2020.1732174 (DOI)000517906100001 ()2-s2.0-85083907794 (Scopus ID)
Available from: 2020-03-19 Created: 2020-03-19 Last updated: 2020-05-20Bibliographically 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
Institute of Electrical and Electronics Engineers, 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: 2019-11-21Bibliographically approved
Danielsson, O., Holm, M. & Syberfeldt, A. (2019). Augmented Reality Smart Glasses for Industrial Assembly Operators: A Meta-Analysis and Categorization. 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, 10–12 September 2019, Queen’s University, Belfast, UK. Paper presented at 17th International Conference on Manufacturing Research, incorporating the 34th National Conference on Manufacturing Research, 10–12 September 2019, Queen’s University, Belfast, UK (pp. 173-179). Amsterdam: IOS Press, 9
Open this publication in new window or tab >>Augmented Reality Smart Glasses for Industrial Assembly Operators: A Meta-Analysis and Categorization
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, 10–12 September 2019, Queen’s University, Belfast, UK / [ed] Yan Jin, Mark Price, Amsterdam: IOS Press, 2019, Vol. 9, p. 173-179Conference paper, Published paper (Refereed)
Abstract [en]

Augmented reality smart glasses (ARSG) are an emerging technology that has the potential to revolutionize how operators interact with information in cyber-physical systems. However, augmented reality is currently not widespread in industrial assembly. The aim of this paper is to investigate and map ARSG in manufacturing from the perspectives of the operator, of manufacturing engineering, and of its technological maturity. This mapping provides an overview of topics relevant to enabling the implementation of ARSG in a manufacturing system, thus facilitating future exploration of the three perspectives. This investigation was done using a meta-analysis of literature reviews of applications of augmented reality in industrial manufacturing. The meta-analysis categorized previously identified topics within augmented reality in industrial manufacturing and mapped those to the scope of the three perspectives.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2019
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 9
Keywords
Augmented Reality, Literature Review, Assembly, Assembly Operators
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-17850 (URN)10.3233/ATDE190031 (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, 10–12 September 2019, Queen’s University, Belfast, UK
Available from: 2019-11-04 Created: 2019-11-04 Last updated: 2020-02-19Bibliographically 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
Syberfeldt, A. & Ekblom, T. (2019). Improved Automatic Quality Inspections through the Integration of State-of-the-Art Machine Vision and Collaborative Robots. 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, 10–12 September 2019, Queen’s University, Belfast, UK (pp. 107-112). Amsterdam: IOS Press, 9
Open this publication in new window or tab >>Improved Automatic Quality Inspections through the Integration of State-of-the-Art Machine Vision and Collaborative Robots
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. 107-112Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we discuss the concepts of a flexible and high-performing solution for automatic quality control that integrates state-of-the-art machine learning algorithms with collaborative robots. The overall aim of the paper is to take the first steps towards improved automatic quality inspections in the manufacturing industry, leading to reduced quality defects and reduced costs in the manufacturing process. For developing and evaluating a first version of a solution that integrates state-of-the-art machine vision and collaborative robots we use a real-world case study focusing on improved quality inspection. Results from the case study shows that it is possible to realize automatic quality inspections through the use of a collaborative robot as intended, but also that there are some challenges that need to be further addressed in order to achieve a top-performing system.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2019
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 9
Keywords
Industrial Quality Control, Machine Vision, Collaborative Robot
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-18222 (URN)10.3233/ATDE190020 (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, 10–12 September 2019, Queen’s University, Belfast, UK
Available from: 2020-02-25 Created: 2020-02-25 Last updated: 2020-04-22Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-3973-3394

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