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  • 1.
    Andersson, Marcus
    et al.
    University of Skövde, School of Technology and Society.
    Grimm, Henrik
    University of Skövde, School of Technology and Society.
    Persson, Anna
    University of Skövde, School of Technology and Society.
    Ng, Amos
    University of Skövde, School of Technology and Society.
    A web-based simulation optimization system for industrial scheduling2007In: Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come, IEEE Press, 2007, p. 1844-1852Conference paper (Refereed)
    Abstract [en]

    Many real-world production systems are complex in nature and it is a real challenge to find an efficient scheduling method that satisfies the production requirements as well as utilizes the resources efficiently. Tools like discrete event simulation (DES) are very useful for modeling these systems and can be used to test and compare different schedules before dispatching the best schedules to the targeted systems. DES alone, however, cannot be used to find the "optimal" schedule. Simulation-based optimization (SO) can be used to search for optimal schedules efficiently without too much user intervention. Observing that long computing time may prohibit the interest in using SO for industrial scheduling, various techniques to speed up the SO process have to be explored. This paper presents a case study that shows the use of a Web-based parallel and distributed SO platform to support the operations scheduling of a machining line in an automotive factory.

  • 2.
    Andersson, Marcus
    et al.
    University of Skövde, School of Technology and Society.
    Persson, Anna
    University of Skövde, School of Technology and Society.
    Grimm, Henrik
    University of Skövde, School of Technology and Society.
    Ng, Amos
    University of Skövde, School of Technology and Society.
    Simulation-based Scheduling using a Genetic Algorithm with Consideration to Robustness: A Real-world Case Study2007In: Proceedings of the 17th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM 2007), 2007, p. 957-964Conference paper (Refereed)
  • 3.
    Andersson, Martin
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Bandaru, Sunith
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Parameter tuned CMA-ES on the CEC'15 expensive problems2015In: Evolutionary Computation, IEEE conference proceedings, 2015, p. 1950-1957Conference paper (Refereed)
    Abstract [en]

    Evolutionary optimization algorithms have parameters that are used to adapt the search strategy to suit different optimization problems. Selecting the optimal parameter values for a given problem is difficult without a-priori knowledge. Experimental studies can provide this knowledge by finding the best parameter values for a specific set of problems. This knowledge can also be constructed into heuristics (rule-of-thumbs) that can adapt the parameters for the problem. The aim of this paper is to assess the heuristics of the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) optimization algorithm. This is accomplished by tuning CMA-ES parameters so as to maximize its performance on the CEC'15 problems, using a bilevel optimization approach that searches for the optimal parameter values. The optimized parameter values are compared against the parameter values suggested by the heuristics. The difference between specialized and generalized parameter values are also investigated.

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  • 4.
    Andersson, Martin
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Bandaru, Sunith
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Parameter Tuning of MOEAs Using a Bilevel Optimization Approach2015In: Evolutionary Multi-Criterion Optimization: 8th International Conference, EMO 2015, Guimarães, Portugal, March 29 --April 1, 2015. Proceedings, Part I / [ed] António Gaspar-Cunha, Carlos Henggeler Antunes & Carlos Coello Coello, Springer International Publishing Switzerland , 2015, p. 233-247Conference paper (Refereed)
    Abstract [en]

    The performance of an Evolutionary Algorithm (EA) can be greatly influenced by its parameters. The optimal parameter settings are also not necessarily the same across different problems. Finding the optimal set of parameters is therefore a difficult and often time-consuming task. This paper presents results of parameter tuning experiments on the NSGA-II and NSGA-III algorithms using the ZDT test problems. The aim is to gain new insights on the characteristics of the optimal parameter settings and to study if the parameters impose the same effect on both NSGA-II and NSGA-III. The experiments also aim at testing if the rule of thumb that the mutation probability should be set to one divided by the number of decision variables is a good heuristic on the ZDT problems. A comparison of the performance of NSGA-II and NSGA-III on the ZDT problems is also made.

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  • 5.
    Andersson, Martin
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Bengtsson, Victor
    Posten AB, Solna, Sweden.
    Evolutionary Simulation Optimization of Personnel Scheduling2014In: 12th International Industrial Simulation Conference 2014: ISC'2014 / [ed] Amos Ng; Anna Syberfeldt, Eurosis , 2014, p. 61-65Conference paper (Refereed)
    Abstract [en]

    This paper presents a simulation-optimization system for personnel scheduling. The system is developed for the Swedish postal services and aims at finding personnel schedules that minimizes both total man hours and the administrative burden of the person responsible for handling schedules. For the optimization, the multi-objective evolutionary algorithm NSGA-II is implemented. The simulation-optimization system is evaluated on a real-world test case and results from the evaluation shows that the algorithm is successful in optimizing the problem.

  • 6.
    Aslam, Tehseen
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Pehrsson, Leif
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Volvo Car Engine, Manufacturing Research and Concepts, Skövde, Sweden.
    Urenda-Moris, Mathias
    Uppsala University, Ångströmlaboratoriet, Uppsala, Sweden.
    Towards an industrial testbed for holistic virtual production development2018In: 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 (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.

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  • 7.
    Danielsson, Oscar
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Holm, Magnus
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Augmented Reality Smart Glasses for Industrial Assembly Operators: A Meta-Analysis and Categorization2019In: 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 (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.

  • 8.
    Danielsson, Oscar
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Holm, Magnus
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Augmented reality smart glasses for operators in production: Survey of relevant categories for supporting operators2020In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 93, p. 1298-1303Article in journal (Refereed)
    Abstract [en]

    The aim of this paper is to give an overview of the current knowledge and future challenges of augmented reality smart glasses (ARSG) for use by industrial operators. This is accomplished through a survey of the operator perspective of ARSG for industrial application, aiming for faster implementation of ARSG for operators in manufacturing. The survey considers the categories assembly instructions, human factors, design, support, and training from the operator perspective to provide insights for efficient use of ARSG in production. The main findings include a lack of standards in the design of assembly instructions, the field of view of ARSG are limited, and the guidelines for designing instructions focus on presenting context-relevant information and limiting the disturbance of reality. Furthermore, operator task routine is becoming more difficult to achieve and testing has mainly been with non-operator testers and overly simplified tasks. Future challenges identified from the review include: longitudinal user-tests of ARSG, a deeper evaluation of how to distribute the weight of ARSG, further improvement of the sensors and visual recognition to facilitate better interaction, and task complexity is likely to increase.

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  • 9.
    Danielsson, Oscar
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Holm, Magnus
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Augmented reality smart glasses in industrial assembly: Current status and future challenges2020In: Journal of Industrial Information Integration, ISSN 2467-964X, E-ISSN 2452-414X, Vol. 20, article id 100175Article, review/survey (Refereed)
    Abstract [en]

    This article aims to provide a better understanding of Augmented Reality Smart Glasses (ARSG) for assembly operators from two perspectives, namely, manufacturing engineering and technological maturity. A literature survey considers both these perspectives of ARSG. The article's contribution is an investigation of the current status as well as challenges for future development of ARSG regarding usage in the manufacturing industry in relation to the two perspectives. This survey thereby facilitate a better future integration of ARSG in manufacturing. Findings include that commercially available ARSG differ considerably in their hardware specifications. The Technological Readiness Level (TRL) of some of the components of ARSG is still low, with displays having a TRL of 7 and tracking a TRL of 5. A mapping of tracking technologies and their suitability for industrial ARSG was done and identified Bluetooth, micro-electro mechanical sensors (MEMS) and infrared sensors as potentially suitable technologies to improve tracking. Future work identified is to also explore the operator perspective of ARSG in manufacturing. © 2020

  • 10.
    Danielsson, Oscar
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Holm, Magnus
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Evaluation Framework for Augmented Reality Smart Glasses as Assembly Operator Support: Case Study of Tool Implementation2021In: IEEE Access, E-ISSN 2169-3536, Vol. 9, p. 104904-104914Article in journal (Refereed)
    Abstract [en]

    Augmented reality smart glasses (ARSG) have been identified as relevant support tools for the Operator 4.0 paradigm. Although ARSG are starting to be used in industry, their use is not yet widespread. A previously developed online tool based on a framework for evaluating ARSG as assembly operator support is iteratively improved in this paper with expanded functionality. The added functionality consists of practical recommendations for implementing ARSG in production. These recommendations were produced with the help of five focus groups of industrial representatives working in production. The recommendations were evaluated using case studies at three different companies. The recommendations were found to be detailed and a good support for the process of considering ARSG integration into production. The companies overall found the tool and its recommendations to be relevant and correct for their cases.

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  • 11.
    Danielsson, Oscar
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Brewster, Rodney
    Volvo Car Corporation, Skövde, Sweden.
    Wang, Lihui
    KTH Royal Institute of Technology, Kungliga Tekniska högskolan, Stockholm.
    Assessing Instructions in Augmented Reality for Human-Robot Collaborative Assembly by Using Demonstrators2017In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 63, p. 89-94Article in journal (Refereed)
    Abstract [en]

    Robots are becoming more adaptive and aware of their surroundings. This has opened up the research area of tight human-robot collaboration,where humans and robots work directly interconnected rather than in separate cells. The manufacturing industry is in constant need ofdeveloping new products. This means that operators are in constant need of learning new ways of manufacturing. If instructions to operatorsand interaction between operators and robots can be virtualized this has the potential of being more modifiable and available to the operators.Augmented Reality has previously shown to be effective in giving operators instructions in assembly, but there are still knowledge gapsregarding evaluation and general design guidelines. This paper has two aims. Firstly it aims to assess if demonstrators can be used to simulatehuman-robot collaboration. Secondly it aims to assess if Augmented Reality-based interfaces can be used to guide test-persons through apreviously unknown assembly procedure. The long-term goal of the demonstrator is to function as a test-module for how to efficiently instructoperators collaborating with a robot. Pilot-tests have shown that Augmented Reality instructions can give enough information for untrainedworkers to perform simple assembly-tasks where parts of the steps are done with direct collaboration with a robot. Misunderstandings of theinstructions from the test-persons led to multiple errors during assembly so future research is needed in how to efficiently design instructions.

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  • 12.
    Danielsson, Oscar
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Holm, Magnus
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Thorvald, Peter
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Integration of Augmented Reality Smart Glasses as Assembly Support: A Framework Implementation in a Quick Evaluation Tool2023In: International Journal of Manufacturing Research, ISSN 1750-0591, Vol. 18, no 2, p. 144-164Article in journal (Refereed)
    Abstract [en]

    Augmented reality smart glasses (ARSG) have been successfully used as operator support in production. However, their use is not yet widespread, likely in part due to a lack of knowledge about how to integrate ARSG into production. This lack of knowledge can also make it hard to estimate whether this is a worthwhile investment. Our solution is to provide an online evaluation tool to help production planners estimate the likelihood that ARSG will be worth the investment cost in specific production cases. Based on a strawman design, multiple design iterations were followed by a pilot test performed by participants from different manufacturing companies involved in planning production for operators. A Likert scale survey was used to evaluate the tool. The results show a slightly positive evaluation of the tool with suggestions for improvement, including widening the scope and granularity of the tool. Future works include further iterations and case studies.

  • 13.
    Danielsson, Oscar
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Holm, Magnus
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Wang, Lihui
    KTH Royal Institue of Technology, Stockholm, Sweden.
    Operators perspective on augmented reality as a support tool in engine assembly2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 45-50Article in journal (Refereed)
    Abstract [en]

    Augmented Reality (AR) has shown its potential in supporting operators in manufacturing. AR-glasses as a platform both in industrial use are emerging markets, thereby making portable and hands-free AR more and more feasible. An important aspect of integrating AR as a support tool for operators is their acceptance of the technology. This paper presents the results of interviewing operators regarding their view on AR technology in their field and observing them working in automotive engine assembly and how they interact with current instructions. The observations and follow-up questions identified three main aspects of the information that the operators looked at: validating screw torque, their current assembly time, and if something went wrong. The interviews showed that a large amount of the operators were positive towards using AR in assembly. This has given an insight in both the current information interaction the operators do and their view on the potential in using AR. Based on these insights we suggest a mock-up design of an AR-interface for engine assembly to serve as a base for future prototype designs.

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  • 14.
    Despeisse, Mélanie
    et al.
    Chalmers University of Technology, Gothenburg, Sweden.
    Chari, Arpita
    Chalmers University of Technology, Gothenburg, Sweden.
    González Chávez, Clarissa Alejandra
    Chalmers University of Technology, Gothenburg, Sweden.
    Chen, Xiaoxia
    Chalmers University of Technology, Gothenburg, Sweden.
    Johansson, Björn
    Chalmers University of Technology, Gothenburg, Sweden.
    Igelmo Garcia, Victor
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Abdulfatah, Tarek
    Volvo Group Trucks Operations, Gothenburg, Sweden.
    Polukeev, Alexey
    Lund University, Sweden.
    Achieving Circular and Efficient Production Systems: Emerging Challenges from Industrial Cases2021In: Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems: IFIP WG 5.7 International Conference, APMS 2021, Nantes, France, September 5–9, 2021, Proceedings, Part IV / [ed] Alexandre Dolgui; Alain Bernard; David Lemoine; Gregor von Cieminski; David Romero, Cham: Springer, 2021, p. 523-533Conference paper (Refereed)
    Abstract [en]

    As the need for more responsible production and consumption grows quickly, so does the interest in the concepts of eco-efficiency and circularity. To make swift progress towards sustainability, solutions must be developed and deployed at scale. It is therefore critical to understand the challenges faced by industry to accelerate the uptake of best practices for circular and efficient production systems. This paper presents the emerging issues from three industrial pilots in an on-going collaborative project. We discuss and suggest further work around crucial questions such as: How to deploy circular solutions from lab to industrial scale? How can digitalization support efficient circular processes?. 

  • 15.
    Fathi, Masood
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ghobakhloo, Morteza
    Department of Industrial Engineering, Minab Higher Education Center, University of Hormozgan, Bandar Abbas, Iran / Modern Technology Development and Implementation Research Center, University of Hormozgan, Bandar Abbas, Iran.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    An Interpretive Structural Modeling of Teamwork Training in Higher Education2019In: Education Sciences, E-ISSN 2227-7102, Vol. 9, no 1, p. 1-20Article in journal (Refereed)
    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.

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  • 16.
    Fathi, Masood
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Nourmohammadi, Amir
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    An optimization model for balancing assembly lines with stochastic task times and zoning constraints2019In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 32537-32550, article id 8663269Article in journal (Refereed)
    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.

  • 17.
    Fathi, Masood
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Nourmohammadi, Amir
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Eskandari, Hamidreza
    Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran.
    An improved genetic algorithm with variable neighborhood search to solve the assembly line balancing problem2020In: Engineering computations, ISSN 0264-4401, E-ISSN 1758-7077, Vol. 37, no 2, p. 501-521Article in journal (Refereed)
    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.
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  • 18.
    Fathi, Masood
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ghobakhloo, Morteza
    University of Hormozgan, Bandar Abbas, Iran.
    Eskandari, Hamidreza
    Tarbiat Modares University, Tehran, Iran.
    An optimization model for material supply scheduling at mixed-model assembly lines2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 6p. 1258-1263Article in journal (Refereed)
    Abstract [en]

    This study is motivated by a real case study and addresses the material supply problem at assembly lines. The aim of the study is to optimally schedule the delivery of raw material at assembly lines while using the minimum number of vehicles. To cope with the problem an original mixed integer linear programming model has been proposed based on the assumptions and constraints observed in the case study. The validity of the model has been examined by solving several real cases and analysing different scenarios. The results of the study show the efficiency and effectiveness of the model.

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  • 19.
    Flores Garcia, Erik
    et al.
    Mälardalen University, Eskilstuna, Sweden.
    Ruiz Zúñiga, Enrique
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Bruch, Jessica
    Mälardalen University, Eskilstuna, Sweden.
    Urenda Moris, Matias
    Division of Industrial Engineering and Management, University of Uppsala, Uppsala, Sweden.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Simulation-based Optimization for Facility Layout Design in Conditions of High Uncertainty2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 334-339Article in journal (Refereed)
    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.

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  • 20.
    Fornlöf, Veronica
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. GKN Aerospace.Engine Systems.
    Galar, Diego
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Almgren, Torgny
    GKN Aerospace Engine Systems.
    Aircraft engines: A maintenance trade-off in a complex system2015Conference paper (Refereed)
    Abstract [en]

    An aircraft engine is a system of systems with several degrees of complexity. It is important to perform the correct amount of maintenance at each individual maintenance event. A mathematical replacement model is used to ensure that the correct amount of maintenance is performed. However, this paper shows that the reliability of this model could be improved if there were a better way to estimate the life length of on-condition maintained engine parts.

  • 21.
    Fornlöf, Veronica
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. GKN Aerospace.
    Galar, Diego
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Luleå University of Technology.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Almgren, Torgny
    GKN Aerospace.
    On-Condition Parts versus life limited parts: A trade off in aircraft engines2016In: Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective / [ed] U. Kumar, A. Ahmadi, A. K. Verma & P. Varde, 2016, p. 253-262Conference paper (Refereed)
  • 22.
    Fornlöf, Veronica
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. GKN Aerospace Engine Systems, Trollhättan, Sweden.
    Galar, Diego
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Almgren, Torgny
    GKN Aerospace Engine Systems, Trollhättan, Sweden.
    RUL estimation and maintenance optimization for aircraft engines: A system of system approach2016In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 7, no 4, p. 450-461Article in journal (Refereed)
    Abstract [en]

    An aircraft engine is a system of systems with several degrees of complexity. It is important to perform the correct amount of maintenance at each individual maintenance event. A mathematical replacement model is used to ensure that the correct maintenance is performed. The reliability of the results from the mathematical replacement model will be improved if there is a better way to estimate the life length for on-condition engine parts.

  • 23.
    Fornlöf, Veronica
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Galar, Diego
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Almgren, Torgny
    GKN Aerospace Engine Systems, Trollhättan, Sweden.
    Catelani, Marcantonio
    Department of Information Engineering, University of Florence, Florence, Italy.
    Ciani, Lorenzo
    Department of Information Engineering, University of Florence, Florence, Italy.
    Maintenance, prognostics and diagnostics approaches for aircraft engines2016In: 3rd IEEE International Workshop on Metrology for Aerospace, MetroAeroSpace 2016: Proceedings, IEEE, 2016, p. 403-407Conference paper (Refereed)
    Abstract [en]

    In avionics application one of the most important competition factors is the reliability, given that the failure occurrence may leads to a critical state for the functioning of the aircraft. Different maintenance, prognostics and diagnostics approaches are possible with the final aim to optimize both system's availability and safety. Aircraft engines represent a safety critical part of the airplane. For this reason it is a key issue to allocate the proper amount of maintenance at each individual maintenance event. In this paper a mathematical replacement model is proposed to guarantee that the correct amount of maintenance is performed.

  • 24.
    Fornlöf, Veronica
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. GKN.
    Sandberg, Ulf
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Almgren, Torgny
    GKN Aerospace Engine Systems.
    More reliable aircraft engine maintenance optimization by a classification framework for on-condition parts2014In: Proceedings of the 6th Swedish Production Symposium, SPS14, Gothenburg, Sweden, Chalmers , 2014Conference paper (Refereed)
  • 25.
    Frantzén, Marcus
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Holm, Magnus
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Karlsson, V.
    Volvo Group Trucks Operations, Powertrain Production Skövde, Skövde, Sweden.
    Bremert, M.
    Volvo Group Trucks Operations, Powertrain Production Skövde, Skövde, Sweden.
    Dynamic maintenance priority of a real-world machining line2016In: Proceedings of the 7th Swedish Production Symposium, 2016Conference paper (Refereed)
    Abstract [en]

    To support the shop-floor operators, decision support systems (DSS) are becoming more and more vital to the success of manufacturing systems in industry today. In order to get a DSS able to adapt to disturbances in a production system, on-line data are needed to be able to make optimal or near-optimal decisions in real-time (soft real-time). This paper investigates one part of such a system, i.e. how different priorities of maintenance activities (planned and unplanned) affect the productivity of a production system. A discrete-event simulation model has been built for a real-world machining line in order to simulate the decisions made in subject to disturbances. This paper presents a way of prioritizing operators and machines based on multiple criteria such as competence, utilization, distance, bottleneck, and Work-In-Process. An experimental study based on the real-world production system has shown promising results and given insights of how to prioritize the operators in a good way. Another novelty introduced in this paper is the use of simulation-based optimization to generate composite dispatching rules in order to find good tradeoffs when taking a decision of which machine or operator to select.

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    fulltext
  • 26.
    Garcia, Erik Flores
    et al.
    Mälardalen Univ, Box 325, S-63105 Eskilstuna, Sweden..
    Zuniga, Enrique Ruiz
    Univ Skövde, Prod & Automat Engn Div, Box 408, S-54128 Skövde, Sweden..
    Bruch, Jessica
    Mälardalen Univ, Box 325, S-63105 Eskilstuna, Sweden..
    Moris, Matias Urenda
    Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Civil and Industrial Engineering, Industrial Engineering and Management.
    Syberfeldt, Anna
    Univ Skövde, Prod & Automat Engn Div, Box 408, S-54128 Skövde, Sweden..
    Simulation-based Optimization for Facility Layout Design in Conditions of High Uncertainty2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 334-339Article in journal (Refereed)
    Abstract [en]

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

    Download full text (pdf)
    fulltext
  • 27.
    Garcia Rivera, Francisco
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Brolin, Erik
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Iriondo Pascual, Aitor
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Perez Luque, Estela
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Using Virtual Reality and Smart Textiles to Assess the Design of Workstations2020In: SPS2020: Proceedings of the Swedish Production Symposium, October 7–8, 2020 / [ed] Kristina Säfsten, Fredrik Elgh, Amsterdam: IOS Press, 2020, Vol. 13, p. 145-154Conference paper (Refereed)
    Abstract [en]

    This paper presents a solution that integrates a smart textiles systemwith virtual reality to assess the design of workstations from an ergonomics pointof view. By using the system, ergonomists, designers, engineers, and operators,can test design proposals of workstations in an immersive virtual environmentwhile they see their ergonomics evaluation results displayed in real-time.. Thesystem allows its users to evaluate the ergonomics of the workplace in a preproduction phase. The workstation design can be modified, enabling workstationdesigners to better understand, test and evaluate how to create successfulworkstation designs, eventually to be used by the operators in production. Thisapproach uses motion capture together with virtual reality and is aimed tocomplement and integrate with the use of digital human modelling (DHM)software at virtual stages of the production development process.

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    fulltext
  • 28.
    Gustavsson, Patrik
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Holm, Magnus
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Wang, Lihui
    KTH Royal Institute of Technology, Kungliga Tekniska Högskolan, Stockholm.
    Human-robot collaboration – towards new metrics for selection of communication technologies2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 6p. 123-128Article in journal (Refereed)
    Abstract [en]

    Industrial robot manufacturers have in recent years developed collaborative robots and these gains more and more interest within the manufacturing industry. Collaborative robots ensure that humans and robots can work together without the robot being dangerous for the human. However, collaborative robots themselves are not enough to achieve collaboration between a human and a robot; collaboration is only possible if a proper communication between the human and the robot can be achieved. The aim of this paper is to identify and categorize technologies that can be used to enable such communication between a human and an industrial robot.

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  • 29.
    Gustavsson, Patrik
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    A New Algorithm Using the Non-dominated Tree to improve Non-dominated Sorting2018In: Evolutionary Computation, ISSN 1063-6560, E-ISSN 1530-9304, Vol. 26, no 1, p. 89-116Article in journal (Refereed)
    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.

  • 30.
    Gustavsson, Patrik
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    The Industry’s Perspective of Suitable Tasks for Human-Robot Collaboration in Assembly Manufacturing2021In: 11th International Conference on Manufacturing Science and Technology (ICMST 2020) 22nd-24th September 2020, Liverpool, UK, Institute of Physics Publishing (IOPP), 2021, article id 012010Conference paper (Refereed)
    Abstract [en]

    Human-robot collaboration (HRC) is the concept of combining a human and a robot into the same production cell and utilize the benefits of both. This concept has existed for more than a decade, but there are still quite few implementations of HRC within the manufacturing industry. One reason for this is the lack of knowledge when it comes to suitable tasks for HRC. Current research studies on the topic are mainly based on theoretical reasoning and/or research experiments, and little is known about what the industry perceive as suitable tasks for HRC. Therefore, this paper aims to investigate this and find out what industrial actors thinks are the most value-adding tasks for a human and a robot to carry out together. An in-depth interview study is undertaken with two companies and shop-floor operators, production engineers and automation engineers are interviewed. The result of the study pinpoints a number of tasks that the companies thinks are beneficial for HRC, which can serve as a guideline for other manufacturing companies considering to implement HRC.

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    fulltext
  • 31.
    Gustavsson, Patrik
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Brewster, Rodney
    Volvo Car Corporation, Skövde, Sweden.
    Wang, Lihui
    KTH Royal Institute of Technology, Stockholm, Sweden.
    Human-Robot Collaboration Demonstrator Combining Speech Recognition and Haptic Control2017In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 63, p. 396-401Article in journal (Refereed)
    Abstract [en]

    In recent years human-robot collaboration has been an important topic in manufacturing industries. By introducing robots into the same working cell as humans, the advantages of both humans and robots can be utilized. A robot can handle heavy lifting, repetitive and high accuracy tasks while a human can handle tasks that require the flexibility of humans. If a worker is to collaborate with a robot it is important to have an intuitive way of communicating with the robot. Currently, the way of interacting with a robot is through a teaching pendant, where the robot is controlled using buttons or a joystick. However, speech and touch are two communication methods natural to humans, where speech recognition and haptic control technologies can be used to interpret these communication methods. These technologies have been heavily researched in several research areas, including human-robot interaction. However, research of combining these two technologies to achieve a more natural communication in industrial human-robot collaboration is limited. A demonstrator has thus been developed which includes both speech recognition and haptic control technologies to control a collaborative robot from Universal Robots. This demonstrator will function as an experimental platform to further research on how the speech recognition and haptic control can be used in human-robot collaboration. The demonstrator has proven that the two technologies can be integrated with a collaborative industrial robot, where the human and the robot collaborate to assemble a simple car model. The demonstrator has been used in public appearances and a pilot study, which have contributed in further improvements of the demonstrator. Further research will focus on making the communication more intuitive for the human and the demonstrator will be used as the platform for continued research.

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    fulltext
  • 32.
    Gustavsson, Patrik
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Holm, Magnus
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Virtual reality platform for design and evaluation of human-robot collaboration in assembly manufacturing2023In: International Journal of Manufacturing Research, ISSN 1750-0591, Vol. 18, no 1, p. 28-49Article in journal (Refereed)
    Abstract [en]

    This paper presents 'virtual collaborative robot', a virtual reality platform for designing and evaluating collaboration between operators and industrial robots. Within the platform, human-robot collaboration scenarios can be created and a user can interact with a robot without the safety risks that might arise with physical industrial robots. In an initial evaluation of the platform a scenario was implemented combining speech recognition, haptic control, and augmented reality to assemble a car model. The results from this evaluation indicate that the suggested platform can be used to successfully test new applications with the standard equipment of virtual reality headsets.

  • 33.
    Holm, Magnus
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Danielsson, Oscar
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Moore, Philip
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Wang, Lihui
    Sustainable Manufacturing, KTH Royal Institute of Technology, Kungliga Tekniska Högskolan, Stockholm.
    Adaptive instructions to novice shop-floor operators using Augmented Reality2017In: Journal of Industrial and Production Engineering, ISSN 2168-1015, Vol. 34, no 5, p. 362-374Article in journal (Refereed)
    Abstract [en]

    This paper presents a novel system using Augmented Reality and Expert Systems to enhance the quality and efficiency of shop-floor operators. The novel system proposed provides an adaptive tool that facilitates and enhances support on the shop-floor, due to its ability to dynamically customize the instructions displayed, dependent upon the competence of the user. A comparative study has been made between an existing method of quality control instructions at a machining line in an automotive engine plant and this novel system. It has been shown that the new approach outcompetes the existing system, not only in terms of perceived usability but also with respect to two other important shop-floor variables: quality and productivity. Along with previous research, the outcomes of these test cases indicate the value of using Augmented Reality technology to enhance shop-floor operators’ ability to learn and master new tasks.

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    fulltext
  • 34.
    Holm, Magnus
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. ASSAR Industrial Innovation Arena, Skövde, Sweden.
    Ng, Amos H. C.University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management at Uppsala University, Sweden ; Evoma AB, Skövde, Sweden.Högberg, DanUniversity of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Swedish Production Academy, Product Development Academy in Sweden ; International Ergonomics Association (IEA) Technical Committee on Human Simulation and Virtual Environments, Geneva, Switzerland.Syberfeldt, AnnaUniversity of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Special Issue: Digital Transformation Towards a Sustainable Human Centric and Resilient Production2023Collection (editor) (Refereed)
    Abstract [en]

    The realisation of a successful product requires collaboration between developers andproducers, taking account of stakeholder value, reinforcing the contribution of industry tosociety and enhancing the wellbeing of workers while respecting planetary boundaries.Founded in 2006, the Swedish Production Academy (SPA) aims to drive and developproduction research and education and to increase cooperation within the production area.SPA initiated and hosts the conference Swedish Production Symposium. This specialissue is based on invited papers from the 10th Swedish Production Symposium(SPS2022), held in Skövde, Sweden, from 26–29 April 2022. The overall theme forSPS2022 was ‘Industry 5.0 transformation – towards a sustainable, human-centric, andresilient production’.As stated by the European Commission the vision of Industry 5.0 recognises societalgoals. It goes beyond a techno-economic vision, industrial value chains and growthaiming for the industry to become a resilient provider of prosperity, respecting ourplanets boundaries, and placing the industrial worker, her well-being, at the centre of theproduction process.In this special issue, we set out to explore the transition to a resilient, sustainable andhuman centric industry. The first paper explores the need for a joint strategical vision thatinclude technology (selection, development, and implementation), organisation(structure, agility, management, stakeholder collaborations, work environment) andpeople (skills and competences, participation, innovation and creative collaborativeculture, and change readiness), to achieve a resilient and sustainable production systemeffectively and efficiently. The second paper discusses how reconfigurable manufacturingsystems can enable sustainable manufacturing and circularity, achieving highresponsiveness and cost efficiency. The third paper, a synthesis of universal workplacedesign in assembly, explores how human assembly workplaces can be designed in abetter way in regard to inclusion of diverse worker populations. The fourth paperdiscusses different meanings of digital transformation in manufacturing industry fromboth a theoretical and industrial perspective. The fifth paper explores challenges to designa product service system at an SME as an approach to support transition to Industry 5.0.The concluding paper in this special issue discusses a knowledge extraction platform forreproducible decision support based on data from multi-objective experiments.The organiser of SPS2022 has found these six outstanding papers to perfectly alignwith the theme ‘Industry 5.0 transformation’ and express their gratitude to theEditor-in-Chief of IJMR for accepting them for publication in this special issue.

  • 35.
    Holmgren, Noél
    et al.
    Högskolan i Skövde, Institutionen för vård och natur.
    Kazemi, Ali
    Högskolan i Skövde, Institutionen för teknik och samhälle.
    Persson, Anne
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Niklasson, Lars
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Pihlström, Malin
    Högskolan i Skövde.
    Billing, Anna
    Högskolan i Skövde.
    Nilsson, Ulf-Göran
    Högskolan i Skövde, Högskolebiblioteket.
    Grönborg, Lisa
    Högskolan i Skövde, Högskolebiblioteket.
    Johannesson, Krister
    Högskolan i Skövde, Högskolebiblioteket.
    Syberfeldt, Anna
    Högskolan i Skövde, Institutionen för teknik och samhälle.
    Pehrsson, Leif
    Högskolan i Skövde, Institutionen för teknik och samhälle.
    Tengblad, Stefan
    Högskolan i Skövde, Institutionen för teknik och samhälle.
    Ziemke, Tom
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Nilsson, Pernilla
    Halmstad University, Sweden.
    Elowson, Anne-louise
    Högskolan i Skövde.
    Vizlin, Albina
    Högskolan i Skövde.
    Andersson, Monica
    Högskolan i Skövde.
    Klingspor, Pernilla
    Högskolan i Skövde.
    Blomgren, Lars-Göran
    Högskolan i Skövde.
    Larsson, Matts
    Högskolan i Skövde.
    Taylor, Mario
    Högskolan i Skövde.
    Akersten, Eva
    Högskolan i Skövde, Institutionen för teknik och samhälle.
    Bergh, Ingrid
    Högskolan i Skövde, Institutionen för vård och natur.
    Lundell, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Lindblom, Jessica
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för vård och natur.
    Adolfsson, Josef
    Högskolan i Skövde, Institutionen för teknik och samhälle.
    Assessment of Research and Collaboration 20132013Report (Other (popular science, discussion, etc.))
  • 36.
    Holmgren, Noél
    et al.
    University of Skövde, School of Life Sciences.
    Kazemi, Ali
    University of Skövde, School of Technology and Society.
    Persson, Anne
    University of Skövde, School of Humanities and Informatics.
    Niklasson, Lars
    University of Skövde, School of Humanities and Informatics.
    Pihlström, Malin
    University of Skövde.
    Billing, Anna
    University of Skövde.
    Nilsson, Ulf-Göran
    University of Skövde, University library.
    Grönborg, Lisa
    University of Skövde, University library.
    Johannesson, Krister
    University of Skövde, University library.
    Syberfeldt, Anna
    University of Skövde, School of Technology and Society.
    Pehrsson, Leif
    University of Skövde, School of Technology and Society.
    Tengblad, Stefan
    University of Skövde, School of Technology and Society.
    Ziemke, Tom
    University of Skövde, School of Humanities and Informatics.
    Nilsson, Pernilla
    Halmstad University, Sweden.
    Elowson, Anne-louise
    University of Skövde.
    Vizlin, Albina
    University of Skövde.
    Andersson, Monica
    University of Skövde.
    Klingspor, Pernilla
    University of Skövde.
    Blomgren, Lars-Göran
    University of Skövde.
    Larsson, Matts
    University of Skövde.
    Taylor, Mario
    University of Skövde.
    Akersten, Eva
    University of Skövde, School of Technology and Society.
    Bergh, Ingrid
    University of Skövde, School of Life Sciences.
    Lundell, Björn
    University of Skövde, School of Humanities and Informatics.
    Lindblom, Jessica
    University of Skövde, School of Humanities and Informatics.
    Olsson, Björn
    University of Skövde, School of Life Sciences.
    Adolfsson, Josef
    University of Skövde, School of Technology and Society.
    Assessment of Research and Collaboration 20132013Report (Other (popular science, discussion, etc.))
    Download full text (pdf)
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  • 37.
    Holmgren, Noél
    et al.
    Högskolan i Skövde, Institutionen för vård och natur.
    Kazemi, Ali
    Högskolan i Skövde, Institutionen för teknik och samhälle.
    Persson, Anne
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Niklasson, Lars
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Pihlström, Malin
    Högskolan i Skövde.
    Billing, Anna
    Högskolan i Skövde.
    Nilsson, Ulf-Göran
    Högskolan i Skövde, Högskolebiblioteket.
    Grönborg, Lisa
    Högskolan i Skövde, Högskolebiblioteket.
    Johannesson, Krister
    Högskolan i Skövde, Högskolebiblioteket.
    Syberfeldt, Anna
    Högskolan i Skövde, Institutionen för teknik och samhälle.
    Pehrsson, Leif
    Högskolan i Skövde, Institutionen för teknik och samhälle.
    Tengblad, Stefan
    Högskolan i Skövde, Institutionen för teknik och samhälle.
    Ziemke, Tom
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Nilsson, Pernilla
    Halmstad University, Sweden.
    Elowson, Anne-louise
    Högskolan i Skövde.
    Vizlin, Albina
    Högskolan i Skövde.
    Andersson, Monica
    Högskolan i Skövde.
    Klingspor, Pernilla
    Högskolan i Skövde.
    Blomgren, Lars-Göran
    Högskolan i Skövde.
    Larsson, Matts
    Högskolan i Skövde.
    Taylor, Mario
    Högskolan i Skövde.
    Akersten, Eva
    Högskolan i Skövde, Institutionen för teknik och samhälle.
    Bergh, Ingrid
    Högskolan i Skövde, Institutionen för vård och natur.
    Lundell, Björn
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Lindblom, Jessica
    Högskolan i Skövde, Institutionen för kommunikation och information.
    Olsson, Björn
    Högskolan i Skövde, Institutionen för vård och natur.
    Adolfsson, Josef
    Högskolan i Skövde, Institutionen för teknik och samhälle.
    Assessment of Research and Collaboration 20132013Report (Other (popular science, discussion, etc.))
  • 38.
    Igelmo, Victor
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Hansson, Jörgen
    University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment.
    Aslam, Tehseen
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Enabling Industrial Mixed Reality Using Digital Continuity: An Experiment Within Remanufacturing2022In: SPS2022: Proceedings of the 10th Swedish Production Symposium / [ed] Amos H. C. Ng; Anna Syberfeldt; Dan Högberg; Magnus Holm, Amsterdam; Berlin; Washington, DC: IOS Press, 2022, p. 497-507Conference paper (Refereed)
    Abstract [en]

    In the digitalisation era, overlaying digital, contextualised information on top of the physical world is essential for an efficient operation. Mixed reality (MR) is a technology designed for this purpose, and it is considered one of the critical drivers of Industry 4.0. This technology has proven to have multiple benefits in the manufacturing area, including improving flexibility, efficacy, and efficiency. Among the challenges that prevent the big-scale implementation of this technology, there is the authoring challenge, which we address by answering the following research questions: (1) “how can we fasten MR authoring in a manufacturing context?” and (2) “how can we reduce the deployment time of industrial MR experiences?”. This paper presents an experiment performed in collaboration with Volvo within the remanufacturing of truck engines. MR seems to be more valuable for remanufacturing than for many other applications in the manufacturing industry, and the authoring challenge appears to be accentuated. In this experiment, product lifecycle management (PLM) tools are used along with internet of things (IoT) platforms and MR devices. This joint system is designed to keep the information up-to-date and ready to be used when needed. Having all the necessary data cascading from the PLM platform to the MR device using IoT prevents information silos and improves the system’s overall reliability. Results from the experiment show how the interconnection of information systems can significantly reduce development and deployment time. Experiment findings include a considerable increment in the complexity of the overall IT system, the need for substantial investment in it, and the necessity of having highly qualified IT staff. The main contribution of this paper is a systematic approach to the design of industrial MR experiences.

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  • 39.
    Igelmo, Victor
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    García Rivera, Francisco
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Peréz Luque, Estela
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Aiding Observational Ergonomic Evaluation Methods Using MOCAP Systems Supported by AI-Based Posture Recognition2020In: DHM2020: Proceedings of the 6th International Digital Human Modeling Symposium, August 31 – September 2, 2020 / [ed] Lars Hanson, Dan Högberg, Erik Brolin, Amsterdam: IOS Press, 2020, p. 419-429Conference paper (Refereed)
    Abstract [en]

    Observational ergonomic evaluation methods have inherent subjectivity. Observers’ assessment results might differ even with the same dataset. While motion capture (MOCAP) systems have improved the speed and the accuracy of motiondata gathering, the algorithms used to compute assessments seem to rely on predefined conditions to perform them. Moreover, the authoring of these conditions is not always clear. Making use of artificial intelligence (AI), along with MOCAP systems, computerized ergonomic assessments can become more alike to human observation and improve over time, given proper training datasets. AI can assist ergonomic experts with posture detection, useful when using methods that require posture definition, such as Ovako Working Posture Assessment System (OWAS). This study aims to prove the usefulness of an AI model when performing ergonomic assessments and to prove the benefits of having a specialized database for current and future AI training. Several algorithms are trained, using Xsens MVN MOCAP datasets, and their performance within a use case is compared. AI algorithms can provide accurate posture predictions. The developed approach aspires to provide with guidelines to perform AI-assisted ergonomic assessment based on observation of multiple workers.

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  • 40.
    Iriondo Pascual, Aitor
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Lämkull, Dan
    Advanced Manufacturing Engineering, Volvo Car Corporation, Göteborg, Sweden.
    Perez Luque, Estela
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Hanson, Lars
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Global Industrial Development, Scania CV AB, Södertälje, Sweden.
    Optimization of Productivity and Worker Well-Being by Using a Multi-Objective Optimization Framework2021In: IISE Transactions on Occupational Ergonomics and Human Factors, ISSN 2472-5838, Vol. 9, no 3-4, p. 143-153Article in journal (Refereed)
    Abstract [en]

    OCCUPATIONAL APPLICATIONS

    Worker well-being and overall system performance are important elements in the design of production lines. However, studies of industry practice show that current design tools are unable to consider concurrently both productivity aspects (e.g., line balancing and cycle time) and worker well-being related aspects (e.g., the risk of musculoskeletal disorders). Current practice also fails to account for anthropometric diversity in the workforce and does not use the potential of multi-objective simulation-based optimization techniques. Accordingly, a framework consisting of a workflow and a digital tool was designed to assist in the proactive design of workstations to accommodate worker well-being and productivity. This framework uses state-of-the-art optimization techniques to make it easier and quicker for designers to find successful workplace design solutions. A case study to demonstrate the framework is provided

    TECHNICAL ABSTRACT

    Rationale: Simulation technologies are used widely in industry as they enable efficient creation, testing, and optimization of the design of products and production systems in virtual worlds. Simulations of productivity and ergonomics help companies to find optimized solutions that maintain profitability, output, quality, and worker well-being. However, these two types of simulations are typically carried out using separate tools, by persons with different roles, with different objectives. Silo effects can result, leading to slow development processes and suboptimal solutions.

    Purpose: This research is related to the realization of a framework that enables the concurrent optimization of worker well-being and productivity. The framework demonstrates how digital human modeling can contribute to Ergonomics 4.0 and support a human factors centered approach in Industry 4.0. The framework also facilitates consideration of anthropometric diversity in the user group.

    Methods: Design and creation methodology was used to create a framework that was applied to a case study, formulated together with industry partners, to demonstrate the functionality of the noted framework.

    Results: The framework workflow has three parts: (1) Problem definition and creation of the optimization model; (2) Optimization process; and (3) Presentation and selection of results. The case study shows how the framework was used to find a workstation design optimized for both productivity and worker well-being for a diverse group of workers.

    Conclusions: The framework presented allows for multi-objective optimizations of both worker well-being and productivity and was successfully applied in a welding gun use case.

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  • 41.
    Iriondo Pascual, Aitor
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Brolin, Erik
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Hanson, Lars
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Scania CV, Södertälje, Sweden.
    Application of Multi-objective Optimization on Ergonomics in Production: A Case Study2020In: 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, Vol. 975, p. 584-594Conference 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. 

  • 42.
    Iriondo Pascual, Aitor
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Brolin, Erik
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Hanson, Lars
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Scania CV, Södertälje, Sweden.
    Optimizing Ergonomics and Productivity by Connecting Digital Human Modeling and Production Flow Simulation Software2020In: SPS2020: Proceedings of the Swedish Production Symposium, October 7–8, 2020 / [ed] Kristina Säfsten; Fredrik Elgh, Amsterdam: IOS Press, 2020, , p. 679p. 193-204Conference paper (Refereed)
    Abstract [en]

    Simulation software is used in the production development process to simulate production and predict behaviors, calculate times, and plan production in advance. Digital human modeling (DHM) software is used to simulate humans working in production and assess whether workstation designs offer appropriate ergonomic conditions for the workers. However, these human simulations are usually carried out by human factors engineers or ergonomists, whereas the production simulations are carried out by production engineers. Lack of integration of these two simulations can lead to suboptimal solutions when the factory is not optimized to improve both productivity and ergonomics. To tackle this problem, a platform has been developed that connects production flow simulation software data and DHM software data and integrates them in a generic software for data treatment and visualization. Production flow simulation software data and DHM software data are organized in a hierarchical structure that allows synchronization between the production data and the ergonomic data on the target simulation software. The platform is generic and can be connected to any production flow simulation software and any DHM software by creating specific links for each software. The platform requires only the models of the production line, workstations, and tasks in order to perform the simulations in the target simulation software and collect the simulation results to present the results to the user of the platform. 

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  • 43.
    Iriondo Pascual, Aitor
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Brolin, Erik
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Perez Luque, Estela
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Hanson, Lars
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Scania CV AB, Global Industrial Development, Södertälje, Sweden.
    Lämkull, Dan
    Advanced Manufacturing Engineering, Volvo Car Corporation, Göteborg, Sweden.
    Multi-objective Optimization of Ergonomics and Productivity by Using an Optimization Framework2022In: Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021): Volume V: Methods & Approaches / [ed] Nancy L. Black; W. Patrick Neumann; Ian Noy, Cham: Springer, 2022, p. 374-378Conference paper (Refereed)
    Abstract [en]

    Simulation technologies are widely used in industry as they enable efficient creation, testing, and optimization of the design of products and production systems in virtual worlds, rather than creating,testing, and optimizing prototypes in the physical world. In an industrial production context, simulation of productivity and ergonomics helps companies to find and realize optimized solutions that uphold profitability, output, quality, and worker well-being in their production facilities. However, these two types of simulations are typically carried out using separate software, used by different users, with different objectives. This easily causes silo effects, leading to slow development processes and sub-optimal solutions. This paper reports on research related to the realization of an optimization framework that enables the concurrent optimization of aspects relating to both ergonomics and productivity. The framework is meant to facilitate the inclusion of Ergonomics 4.0 in the Industry 4.0 revolution.

  • 44.
    Iriondo Pascual, Aitor
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    García Rivera, Francisco
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Pérez Luque, Estela
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Hanson, Lars
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Scania CV, Södertälje, Sweden.
    Implementation of Ergonomics Evaluation Methods in a Multi-Objective Optimization Framework2020In: DHM2020: Proceedings of the 6th International Digital Human Modeling Symposium, August 31 - September 2, 2020 / [ed] Lars Hanson, Dan Högberg, Erik Brolin, Amsterdam: IOS Press, 2020, p. 361-371Conference paper (Refereed)
    Abstract [en]

    Simulations of future production systems enable engineers to find effective and efficient design solutions with fewer physical prototypes and fewer reconstructions. This can save development time and money and be more sustainable. Better design solutions can be found by linking simulations to multiobjective optimization methods to optimize multiple design objectives. When production systems involve manual work, humans and human activity should be included in the simulation. This can be done using digital human modeling (DHM) software which simulates humans and human activities and can be used to evaluate ergonomic conditions. This paper addresses challenges related to including existing ergonomics evaluation methods in the optimization framework. This challenge arises because ergonomics evaluation methods are typically developed to enable people to investigate ergonomic conditions by observing real work situations. The methods are rarely developed to be used by computer algorithms to draw conclusions about ergonomic conditions. This paper investigates how to adapt ergonomics evaluation methods to implement the results as objectives in the optimization framework. This paper presents a use case of optimizing a workstation using two different approaches: 1) an observational ergonomics evaluation method, and 2) a direct measurement method. Both approaches optimized two objectives: the average ergonomics results, and the 90th percentile ergonomics results.

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  • 45.
    Iriondo Pascual, Aitor
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Lind, Andreas
    Scania CV, Södertälje, Sweden.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Hanson, Lars
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Scania CV, Södertälje, Sweden.
    Enabling Concurrent Multi-Objective Optimization of Worker Well-Being and Productivity in DHM Tools2022In: SPS2022: Proceedings of the 10th Swedish Production Symposium / [ed] Amos H. C. Ng; Anna Syberfeldt; Dan Högberg; Magnus Holm, Amsterdam; Berlin; Washington, DC: IOS Press, 2022, p. 404-414Conference paper (Refereed)
    Abstract [en]

    Work-related musculoskeletal disorders (WMSDs) are often associated with high costs for manufacturing companies and society, as well as negative effects on sustainable working life of workers. To both ensure workers’ well-being and reduce the costs of WMSDs, it is important to consider worker well-being in the design and operations of production processes. To facilitate the simulation of humans in production and improve worker well-being, there are numerous digital human modelling (DHM) tools available on the market. Besides simulation of humans in production, there are numerous production simulation software to simulate production flows of factories, robots and workstations that offer the possibility of improving the productivity of the stations, optimizing the layout and the configuration of the production lines. Despite of the capabilities of DHM and production flow simulation software, there is a lack of tools that can handle an overall optimization perspective, where it is possible to concurrently treat aspects related to both worker well-being and productivity within one tool. This study presents a prescribed tool that enables concurrent multi-objective optimization of worker well-being and productivity in DHM tools by analyzing the impact of different design alternatives. The tool was assessed in a workstation layout optimization use case. In the use case, risk scores of an ergonomics evaluation method was used as a measure of well-being, and total walking distance and workstation area were used as measures of productivity. The results show that the optimized solutions improve both total walking distance, workstation area and ergonomic risk scores compared to the initial solution. This study suggests that the concurrent multi-objective optimization of worker well-being and productivity could generate more optimal solutions for industry and increase the likelihood for a sustainable working life of workers. Therefore, further studies in this field are claimed to be beneficial to industry, society and workers.

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  • 46.
    Iriondo Pascual, Aitor
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Smedberg, Henrik
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Lämkull, Dan
    Advanced Manufacturing Engineering, Volvo Car Corporation, Göteborg, Sweden.
    Enabling Knowledge Discovery in Multi-Objective Optimizations of Worker Well-Being and Productivity2022In: Sustainability, E-ISSN 2071-1050, Vol. 14, no 9, article id 4894Article in journal (Refereed)
    Abstract [en]

    Usually, optimizing productivity and optimizing worker well-being are separate tasks performed by engineers with different roles and goals using different tools. This results in a silo effect which can lead to a slow development process and suboptimal solutions, with one of the objectives, either productivity or worker well-being, being given precedence. Moreover, studies often focus on finding the best solutions for a particular use case, and once solutions have been identified and one has been implemented, the engineers move on to analyzing the next use case. However, the knowledge obtained from previous use cases could be used to find rules of thumb for similar use cases without needing to perform new optimizations. In this study, we employed the use of data mining methods to obtain knowledge from a real-world optimization dataset of multi-objective optimizations of worker well-being and productivity with the aim to identify actionable insights for the current and future optimization cases. Using different analysis and data mining methods on the database revealed rules, as well as the relative importance of the design variables of a workstation. The generated rules have been used to identify measures to improve the welding gun workstation design.

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  • 47.
    Karlsson, Ingemar
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Bandaru, Sunith
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    An interactive decision support system using simulation-based optimization and data mining2015In: Proceedings of the 2015 Winter Simulation Conference / [ed] L. Yilmaz, W. K. V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, IEEE Press, 2015, p. 2112-2123Conference paper (Refereed)
    Abstract [en]

    This paper describes a decision support system (DSS) built on knowledge extraction using simulation-based optimization and data mining. The paper starts with a requirements analysis based on a survey conducted with a number of industrial companies about their practices of using simulations for decision support.Based upon the analysis, a new, interactive DSS that can fulfill the industrial requirements, is proposed.The design of the cloud-based system architecture of the DSS is then described. To show the functionality and potential of the proposed DSS, an application study has been performed for the optimal design of a hypothetical but realistic flexible production cell. How important knowledge with respect to different preferences of the decision maker can be generated as rules, using the new Flexible Pattern Mining algorithm provided in the DSS, will be revealed by the results of this application study.

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    An interactive decision support system using simulation-based optimization and data mining
  • 48.
    Karlsson, Ingemar
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Interactive and Intelligent Decision Support in Manufacturing using Simulation Based Innovization and Cloud Computing2014In: 12th International Industrial Simulation Conference 2014: ISC'2014 / [ed] Amos Ng; Anna Syberfeldt, Eurosis , 2014, p. 69-74Conference paper (Refereed)
    Abstract [en]

    Simulation-based innovization is a method for extracting knowledge from a simulation model and optimization. This method can help decision makers to make high-quality decisions for their manufacturing systems so as to enhance the competitiveness of companies. Nevertheless, the simulation-based innovization process can be computationally costly and having these resources in-house can be expensive. By running the process in a cloud environment instead, the company only pays for the resources they are using. This paper proposes the concept of a cloud-based computing platform that can run the simulation-based innovization process and discuss its possibilities and challenges.

  • 49.
    Land, Niklas
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Almgren, Torgny
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. GKN Aerospace, Stallbacka, Trollhättan, Sweden.
    Vallhagen, Johan
    Volvo Group, Gothenburg, Sweden.
    A Framework for Realizing Industrial Human-Robot Collaboration through Virtual Simulation2020In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 93, p. 1194-1199Article in journal (Refereed)
    Abstract [en]

    Human-Robot Collaboration (HRC) could improve manual labor manufacturing processes by relieving workers of inappropriate operations, such as heavy, repetitive, or manual quality inspections. The literature shows that the greatest challenge for large scale implementation of Human-Robot Collaboration is safety, intuitive interfaces and design methods. We present a comprehensive framework that incorporates the use of virtual simulation for the implementation of Human-Robot Collaboration. The proposed framework defines a development process with five major steps, ending up with a virtual simulation model that can provide a foundation for the physical implementation. The framework has been developed using an automotive industrial case.

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  • 50.
    Land, Niklas
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Almgren, Torgny
    GKN Aerospace Sweden AB, Trollhättan, Sweden.
    Vallhagen, Johan
    Volvo Group Trucks Operations, AB Volvo, Gothenburg, Sweden.
    Virtual Human-Robot Collaboration: The Industry's Perspective on Potential Applications and Benefits2019In: 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 (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.

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