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  • 401.
    Morshedzadeh, Iman
    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.
    Amouzgar, Kaveh
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Management of virtual models with provenance information in the context of product lifecycle management: industrial case studies2019In: Product Lifecycle Management (Volume 4): The Case Studies / [ed] John Stark, Cham: Springer, 2019, 1, p. 153-170Chapter in book (Refereed)
    Abstract [en]

    Using virtual models instead of physical models can help industries reduce the time and cost of developments, despite the time consuming process of building virtual models. Therefore, reusing previously built virtual models instead of starting from scratch can eliminate a large amount of work from users. Is having a virtual model enough to reuse it in another study or task? In most cases, not. Information about the history of that model makes it clear for the users to decide if they can reuse this model or to what extent the model is needed to be modified. A provenance management system (PMS) has been designed to manage provenance information, and it has been used with product lifecycle management system (PLM) and computer-aided technologies (CAx) to save and present historical information about a virtual model. This chapter presents a sequence-based framework of the CAx-PLM-PMS chain and two application case studies considering the implementation of this framework.

  • 402.
    Morshedzadeh, Iman
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Oscarsson, Jan
    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.
    Aslam, Tehseen
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Frantzén, Marcus
    Volvo Car Corporation, Skövde, Sweden.
    Multi-level management of discrete event simulation models in a product lifecycle management framework2018In: Procedia Manufacturing, E-ISSN 2351-9789, Vol. 25, p. 74-81Article in journal (Refereed)
    Abstract [en]

    Discrete event simulation (DES) models imitates the behavior of a production system. Models can be developed to reflect different levels of the production system, e.g supply chain level or manufacturing line level. Product Lifecycle Management (PLM) systems have been developed in order to manage product and manufacturing related data. DES models is one kind of product lifecycle’s data which can be managed by a PLM system. This paper presents a method and its implementation for management of interacting multi-level models utilizing a PLM system.

  • 403.
    Morshedzadeh, Iman
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Oscarsson, Jan
    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.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Sillanpaa, Janne
    InterSystems Sweden AB, Stockholm.
    Product lifecycle management with provenance management and virtual models: an industrial use-case study2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 6p. 1190-1195Article in journal (Refereed)
    Abstract [en]

    Saving and managing virtual models’ provenance information (models’ history) can increase the level of reusability of those models. This paper describes a provenance management system (PMS) that has been developed based on an industrial case study.

    The product lifecycle management (PLM) system, as a main data management system, is responsible for receiving virtual models and their related data from Computer-Aided technologies (CAx) and providing this information for the PMS. In this paper, the management of discrete event simulation data with the PLM system will be demonstrated as the first link of provenance data management chain (CAx-PLM-PMS).

  • 404.
    Morshedzadeh, Iman
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Oscarsson, Jan
    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.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jenefeldt, Anders
    Volvo Cars Corporation, Skövde, Sweden.
    Real World Data Identification and Classification for Support of Virtual Confidence2016Conference paper (Refereed)
    Abstract [en]

    Shortening of the product development process time is one of the main approaches for all enterprises to offer their products to the market. Virtual manufacturing tools can help companies to reduce their time to market, by reduction of the engineering lead time. Extensive use of virtual engineering models results in a need for verification of the model’s accuracy. This virtual engineering usability and assessment have been named virtual confidence. The two main factors of the achievement of this confidence are the accuracy of the virtual models and the virtual engineering results.

    For controlling of both above factors, a complete virtual model and related virtual model knowledge are needed. These knowledges can be tacit or explicit. For exploring explicit knowledge, a data and information collection from different disciplines in the organization is needed.

    In this paper, a data map with focus on the manufacturing engineering scope will be presented. This data map is generated from different data sources at a manufacturing plant, and gives an overview of different data that exist at different data sources, in the area of manufacturing. Combining real world data from different sources with virtual engineering model data supports, amongst others, establishment of virtual confidence.

  • 405.
    Muller, Jasmin
    et al.
    University of Skövde, School of Health and Education. University of Skövde, Health and Education.
    Ekström, Anette
    University of Skövde, School of Health and Education. University of Skövde, Health and Education.
    Harlén, Mikael
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Lindmark, Ulrika
    School of Health Sciences, Jönköping University, Jönköping, Sweden.
    Handlin, Linda
    University of Skövde, School of Health and Education. University of Skövde, Health and Education.
    Mechanical massage and mental training program effect employees' heart rate, blood pressure and fingertip temperature: An exploratory pilot study2016In: European Journal of Integrative Medicine, ISSN 1876-3820, E-ISSN 1876-3839, Vol. 8, no 5, p. 762-768Article in journal (Refereed)
    Abstract [en]

    Introduction: Inability to relax and recover is suggested to be a key factor for stress-related health problems. This study aimed to investigate possible effects of mechanical massage and mental training, used either separately or in combination during working hours. Methods: Employees were randomly assigned to one of the following groups: i) Mechanical massage combined with mental training (n = 19), ii) Mechanical massage (n = 19), iii) Mental training (n = 19), iv) Pause (n = 19), v) Control (n = 17). The study lasted for eight weeks. Heart rate, blood pressure and fingertip temperature were measured at start, after four and after eight weeks. Results: Between-group analysis showed that heart rate differed significantly between the groups after 4 weeks (p = 0.020) and tended to differ after eight weeks (p = 0.072), with lowest levels displayed in the massage group and the control group. Blood pressure and fingertip temperature did not differ between the groups. Within-group analysis showed that mechanical massage decreased heart rate (p = 0.038) and blood pressure (systolic p = 0.019, diastolic p = 0.026) and increased fingertip temperature (p = 0.035). Mental training programs reduced heart rate (p = 0.036). Combining the two methods increased diastolic blood pressure (p = 0.028) and decreased fingertip temperature (p = 0.031). The control group had a significant decrease in systolic blood pressure during the first four weeks of the study (p = 0.038) Conclusion: Receiving mechanical massage and listening to mental training programs, either separately or in combination, during working hours had some positive effects on the employees’ heart rate, blood pressure and fingertip temperature. The effects were especially strong for employees who received mechanical massage only.

  • 406.
    Muller, Jasmin
    et al.
    University of Skövde, School of Health and Education. University of Skövde, Health and Education.
    Handlin, Linda
    University of Skövde, School of Health and Education. University of Skövde, Health and Education.
    Harlén, Mikael
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Lindmark, Ulrika
    Högskolan i Jönköping, Sweden.
    Ekström, Anette
    University of Skövde, School of Health and Education. University of Skövde, Health and Education.
    The value of armchairs in providing mechanical massage and mental relaxation programmes is not established for workplace health promotion2016In: Focus on Alternative and Complementary Therapies, ISSN 1465-3753, E-ISSN 2042-7166, Vol. 21, no 1, p. 44-45Article in journal (Other academic)
  • 407.
    Mårdberg, Peter
    et al.
    Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Gothenburg, Sweden.
    Carlson, Johan S.
    Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Gothenburg, Sweden.
    Bohlin, Robert
    Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Gothenburg, Sweden.
    Delfs, Niclas
    Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Gothenburg, Sweden.
    Gustafsson, Stefan
    Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Gothenburg, Sweden.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Hanson, Lars
    Department of Product and Production Development, Chalmers University of Technology, Gothenburg, Sweden / Industrial Development, Scania CV, Sweden.
    Using a formal high-level language and an automated manikin to automatically generate assembly instructions2014In: International Journal of Human Factors Modelling and Simulation, ISSN 1742-5549, Vol. 4, no 3/4, p. 233-249Article in journal (Refereed)
    Abstract [en]

    This paper presents an approach to automatically generate predetermined motion time system (PMTS) based assembly instruction lists from simulations within digital human modelling (DHM) software. A formal high-level instruction language is used to instruct an automated manikin to perform assembly operations. The manikin, the language and the assembled objects are composed into a discrete model. In a post-computational step, the model is used to construct PMTS instruction lists by mapping the manikin motions, assembled objects and the language instructions onto a set of PMTS keywords. The described approach is implemented in the DHM software IMMA and tested on industrial cases of manual assembly in the automotive industry.

  • 408.
    Mårdberg, Peter
    et al.
    Frauhofer-Chalmers Research Centre for Industrial Mathematics.
    Carlson, Johan S.
    Frauhofer-Chalmers Research Centre for Industrial Mathematics.
    Bohlin, Robert
    Frauhofer-Chalmers Research Centre for Industrial Mathematics.
    Hanson, Lars
    Department of Product and Production Development, Chalmers University of Technology, Gothenburg, Sweden / Industrial Development, Scania CV, Södertälje, Sweden.
    Högberg, Dan
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Using Ergonomic Criteria to Adaptively Define Test Manikins for Design Problems2012In: Advances in Applied Human Modeling and Simulation / [ed] Vincent G. Duffy, Boca Raton: CRC Press, 2012, p. 265-274Chapter in book (Refereed)
    Abstract [en]

    Digital manikins give a powerful aid in evaluating assembly station ergonomics. A proper verification of an assembly station can avoid costly changes that might occur later on due to injuries and discomfort among the workers.

    However, how to select relevant test manikins for an evaluation is a non-trivial task, since the work of identifying which anthropometric variables that are critical is a tedious and time consuming process.

    Usually only a few variables are selected as a base for building the test manikins. Even if there exist Digital Human Modeling (DHM) software which allow the user to evaluate batches of manikins, the designer still have to select the anthropometric variables of those batches. When several dimensions are considered, the designer have to either use a set of predefined manikins, or determine which anthropometric variables to test and generate manikins based on the confidence intervals of these variables.

    When considering more complex assembly tasks, is it then true that these predetermined test manikins cover all the cases, or does there exist manikins that suffer from bad ergonomics even though all the test manikins turned out well?

    In this paper, we propose a new algorithm for automatically building a set of test manikins. The set is iteratively constructed from the ergonomics results obtained by simulating the assembly operation. Different manikins perform the assembly operation and the ergonomics is evaluated. The anthropometric variables which affect the ergonomics are identified and used to iteratively build up the next manikin. In this way the test manikins are always selected throughout the whole set instead of only considering the boundary manikins, or assuming that the same set of predetermined manikins represents the entire set in every assembly operation.

    The algorithm has been compared with a boundary method, and the results shows that the algorithm can find manikins with worse ergonomics than those tested by the boundary method.

  • 409.
    Ng, Amos
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Bernedixen, Jacob
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Urenda Moris, Matias
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Jägstam, Mats
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Factory flow design and analysis using internet-enabled simulation-based optimization and automatic model generation2011In: Proceedings of the 2011 Winter Simulation Conference / [ed] S. Jain, R. Creasey & J. Himmelspach, IEEE conference proceedings, 2011, p. 2176-2188Conference paper (Refereed)
    Abstract [en]

    Despite simulation offers tremendous promise for designing and analyzing complex production systems, manufacturing industry has been less successful in using it as a decision support tool, especially in the early conceptual phase of factory flow design. If simulation is used today for system design, it is more often used in later phases when important design decisions have already been made and costs are locked. With an aim to advocate the use of simulation in early phases of factory design and analysis, this paper introduces FACTS Analyzer, a toolset developed based on the concept of integrating model abstraction, automatic model generation and simulation-based optimization under an innovative Internet-based platform. Specifically, it addresses a novel model aggregation and generation method, which when combined together with other system components, like optimization engines, can synthetically enable simulation to become much easier to use and speed up the time-consuming model building, experimentation and optimization processes, in order to support optimal decision making.

  • 410.
    Ng, Amos
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Deb, Kalyanmoy
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Dudas, Catarina
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Simulation-based Innovization for production systems improvement: An industrial case study2009In: The International 3rd Swedish Production Symposium / [ed] B.-G. Rosén, The Swedish Production Academy , 2009, p. 278-286Conference paper (Refereed)
    Abstract [en]

    This paper introduces a new methodology for the design, analysis, and optimization of production systems. The methodology is based on the Innovization procedure originally introduced for unveiling new and innovative design principles in engineering design problems. Although the Innovization method is based on multi-objective optimization and post-optimality analyses of optimized solutions, it extends the scope beyond an optimization task and attempts to discover new design/operational rules/principles related to decision variables and objectives, in order to enable a deeper understanding of the problem. By integrating the concept of Innovization with discrete-event simulation, a new set of powerful tools can be developed for general systems analysis, which is particularly suitable for production systems. After describing the Simulation-based Innovization procedure and its difference from conventional simulation analysis methods, the results of an industrial case study, carried out for the improvement of an assembly line at an automotive manufacturer in Sweden, are presented.

  • 411.
    Ng, Amos H. C.
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Bernedixen, Jacob
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Volvo Car Corporation, Sweden.
    Pehrsson, Leif
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Volvo Car Corporation, Sweden.
    What Does Multi-Objective Optimization Have to Do with Bottleneck Improvement of Production Systems?2014In: Proceedings of The 6th International Swedish Production Symposium 2014 / [ed] Johan Stahre, Björn Johansson & Mats Björkman, 2014Conference paper (Refereed)
    Abstract [en]

    Bottleneck is a common term used to describe the process/operation/person that constrains the performance of the whole system. Since Goldratt introduced his theory of constraint, not many will argue about the importance of identifying and then improving the bottleneck, in order to improve the performance of the entire system. Nevertheless, there exist various definitions of bottleneck, which make bottleneck identification and improvement not a straightforward task in practice. The theory introduced by Production Systems Engineering (PSE) that the bottleneck of a production line is where the infinitesimal improvement can lead to the largest improvement of the average throughput, has provided an inspirational and rigorous way to understand the nature of bottleneck. This is because it conceptually puts bottleneck identification and improvement into a single task. Nevertheless, it is said that a procedure to evaluate how the efficiency increase of each machine would affect the total performance of a line is hardly possible in most practical situations. But is this true?In this paper, we argue how multi-objective optimization fits nicely into the theory introduced by PSE and hence how it can be developed into a practical bottleneck improvement methodology. Numerical results from a real-world application study on a highly complex machining line are provided to justify the practical applicability of this new methodology.

  • 412.
    Ng, Amos H. C.
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Bernedixen, Jacob
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Syberfeldt, Anna
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    A comparative study of production control mechanisms using simulation-based multi-objective optimisation2012In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 50, no 2, p. 359-377Article in journal (Refereed)
    Abstract [en]

    There exist many studies conducted to compare the performance of different production control mechanisms (PCMs) in order to determine which one performs the best under different conditions. Nonetheless, most of these studies suffer from the problems that the PCMs are not compared with their optimal parameter settings in a truly multi-objective context. This paper describes how different PCMs can be compared under their optimal settings through generating the Pareto-optimal frontiers, in the form of optimal trade-off curves in the performance space, by applying evolutionary multi-objective optimisation to simulation models. This concept is illustrated with a bi-objective comparative study of the four most popular PCMs in the literature, namely Push, Kanban, CONWIP and DBR, on an unbalanced serial flow line in which both control parameters and buffer capacities are to be optimised. Additionally, it introduces the use of normalised hyper-volume as the quantitative metric and confidence-based significant dominance as the statistical analysis method to verify the differences of the PCMs in the performance space. While the results from this unbalanced flow line cannot be generalised, it indicates clearly that a PCM may be preferable in certain regions of the performance space, but not others, which supports the argument that PCM comparative studies have to be performed within a Pareto-based multi-objective context.

  • 413.
    Ng, Amos H. C.
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Dudas, Catarina
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Boström, Henrik
    Stockholm University, Sweden.
    Kalyanmoy, Deb
    Michigan State University, USA.
    Interleaving Innovization with Evolutionary Multi-Objective Optimization in Production System Simulation for Faster ConvergenceOptimization2013In: Learning and Intelligent Optimization: 7th International Conference, LION 7, Catania, Italy, January 7-11, 2013, Revised Selected Papers / [ed] Giuseppe Nicosia, Panos Pardalos, Berlin, Heidelberg: Springer Berlin/Heidelberg, 2013, p. 1-18Chapter in book (Refereed)
    Abstract [en]

    This paper introduces a novel methodology for the optimization, analysis and decision support in production systems engineering. The methodology is based on the innovization procedure, originally introduced to unveil new and innovative design principles in engineering design problems. The innovization procedure stretches beyond an optimization task and attempts to discover new design/operational rules/principles relating to decision variables and objectives, so that a deeper understanding of the underlying problem can be obtained. By integrating the concept of innovization with simulation and data mining techniques, a new set of powerful tools can be developed for general systems analysis. The uniqueness of the approach introduced in this paper lies in that decision rules extracted from the multi-objective optimization using data mining are used to modify the original optimization. Hence, faster convergence to the desired solution of the decision-maker can be achieved. In other words, faster convergence and deeper knowledge of the relationships between the key decision variables and objectives can be obtained by interleaving the multi-objective optimization and data mining process. In this paper, such an interleaved approach is illustrated through a set of experiments carried out on a simulation model developed for a real-world production system analysis problem.

  • 414.
    Ng, Amos H. C.
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Dudas, Catarina
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Nießen, Johannes
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Deb, Kalyanmoy
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Simulation-Based Innovization Using Data Mining for Production Systems Analysis2011In: Multi-objective Evolutionary Optimisation for Product Design and Manufacturing / [ed] Lihui Wang, Amos H. C. Ng, Kalyanmoy Deb, Springer London, 2011, p. 401-429Chapter in book (Refereed)
    Abstract [en]

    This chapter introduces a novel methodology for the analysis and optimization of production systems. The methodology is based on the innovization procedure, originally introduced for unveiling new and innovative design principles in engineering design problems. Although the innovization method is based on multi-objective optimization and post-optimality analyses of optimised solutions, it stretches the scope beyond an optimization task and attempts to discover new design/operational rules/principles relating to decision variables and objectives, so that a deeper understanding of the problem can be obtained. By integrating the concept of innovization with discrete-event simulation and data mining techniques, a new set of powerful tools can be developed for general systems analysis, particularly suitable for production systems. The uniqueness of the integrated approach proposed in this chapter lies on applying data mining to the data sets generated from simulation-based multi-objective optimization, in order to automatically or semi-automatically discover and interpret the hidden relationships and patterns for optimal production systems design/reconfiguration.

  • 415.
    Ng, Amos H. C.
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Dudas, Catarina
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Pehrsson, Leif
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Deb, Kalyanmoy
    University of Skövde, The Virtual Systems Research Centre.
    Knowledge Discovery in Production simulation By Interleaving Multi-Objective Optimization and Data Mining2012In: Proceedings of the SPS12 conference 2012, The Swedish Production Academy , 2012, p. 461-471Conference paper (Refereed)
  • 416.
    Ng, Amos H. C.
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Shaaban, Sabry
    Department of Strategy, ESC La Rochelle, La Rochelle, France.
    Bernedixen, Jacob
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Studying unbalanced workload and buffer allocation of production systems using multi-objective optimisation2017In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 55, no 24, p. 7435-7451Article in journal (Refereed)
    Abstract [en]

    Numerous studies have investigated the effects of unbalanced service times and inter-station buffer sizes on the efficiency of discrete part, unpaced production lines. There are two main disadvantages of many of these studies: (1) only some predetermined degree of imbalance and patterns of imbalance have been evaluated against the perfectly balanced configuration, making it hard to form a general conclusion on these factors; (2) only a single objective has been set as the target, which neglects the fact that different patterns of imbalance may outperform with respect to different performance measures. Therefore, the aim of this study is to introduce a new approach to investigate the performance of unpaced production lines by using multiple-objective optimisation. It has been found by equipping multi-objective optimisation with an efficient, equality constraints handling technique, both the optimal pattern and degree of imbalance, as well as the optimal relationship among these factors and the performance measures of a production system can be sought and analysed with some single optimisation runs. The results have illustrated that some very interesting relationships among the key performance measures studied, including system throughput, work-in-process and average buffer level, could only be observed within a truly multi-objective optimisation context. While these results may not be generalised to apply to any production lines, the genericity of the proposed simulation-based approach is believed to be applicable to study any real-world, complex production lines.

  • 417.
    Ng, Amos H.C.
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. School of Engineering, Jönköping University, Sweden .
    Bandaru, Sunith
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Frantzén, Marcus
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Volvo Car Corporation, Sweden .
    Innovative Design and Analysis of Production Systems by Multi-objective Optimization and Data Mining2016In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 50, p. 665-671Article in journal (Refereed)
    Abstract [en]

    This paper presents an innovative approach for the design and analysis of production systems using multi-objective optimization and data mining. The innovation lies on how these two methods using different computational intelligence algorithms can be synergistically integrated and used interactively by production systems designers to support their design decisions. Unlike ordinary optimization approaches for production systems design which several design objectives are linearly combined into a single mathematical function, multi-objective optimization that can generate multiple design alternatives and sort their performances into an efficient frontier can enable the designer to have a more complete picture about how the design decision variables, like number of machines and buffers, can affect the overall performances of the system. Such kind of knowledge that can be gained by plotting the efficient frontier cannot be sought by single-objective based optimizations. Additionally, because of the multiple optimal design alternatives generated, they constitute a dataset that can be fed into some data mining algorithms for extracting the knowledge about the relationships among the design variables and the objectives. This paper addresses the specific challenges posed by the design of discrete production systems for this integrated optimization and data mining approach and then outline a new interactive data mining algorithm developed to meet these challenges, illustrated with a real-world production line design example.

  • 418.
    Ng, Amos H.C.
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Engineering Science.
    Skoogh, Anders
    Chalmers University of Technology, Gothenburg, Sweden.
    Lämkull, Dan
    Volvo Car Corporation, Gothenburg, Sweden.
    Optimal Maintenance Resources Allocation Using Automated Simulation-based Optimisation and Data Management2015In: Simulation in Production and Logistics 2015 / [ed] Markus Rabe, Uwe Clausen, Stuttgart: Fraunhofer IRB Verlag, 2015, p. 437-446Conference paper (Refereed)
    Abstract [en]

    This paper introduces a Streamlined Modelling and Decision Support (StreaMod) approach in which input data management, simulation model generation/update and simulation-based optimisation are synergistically integrated into a largely automated process. The aim of this automated process is to support decision making related to the optimal maintenance resources allocation that could improve the performance of production/logistics systems. The basic novelty of the StreaMod optimisation methodology lies on the formulation of an optimal maintenance allocation problem of a production/logistic system into a bi-objective optimisation problem, so that optimal resources/changes to improve the throughput of the system can be sought in a single optimisation run. The successful application of this methodology in a real-world automotive factory will also be addressed in this paper.

  • 419.
    Ng, Amos
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Jägstam, Mats
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Pehrsson, Leif
    Volvo Car Corporation.
    Deb, Kalyanmoy
    Indian Institute of Technology Kanpur, India.
    Improving Factory Productivity and Energy Efficiency Through Holistic Simulation Optimisation2011In: The 21st International Conference on Multiple Criteria Decision Making, University of Jyväskylä , 2011, p. 235-Conference paper (Refereed)
    Abstract [en]

    There is an urgent need for the automotive inductry to explore strategies and methods to accelerate the industrial efficiency progress and support decision making in order to regain profitability. At the same time, decision making should not be made strictly from a view of productivity and investment cost. Manufactures worldwide are taking steps towards more sustainable manufacturing. Sustainability, in terms of "Energy Efficiency", "Lean", "Lead Time Efficiency" and other forms of reuse/conservation of resources has become a paramount factor that needs to be considered not only during the operational stage but from the very first day a production system is designed or configured. Therefore, to optimise a manufacturing system today is not only about maximising capacity and minimising costs, it is also about minimising energy use, minimising loss, minimising manufacturing lead time and other sustainability measures. The aim of the presentation is to introduce an innovative simulation-based optimisation and knowledge elicitation methodology for decision-making support within the production systems lifecycle to increase the profitability (increasing cost effectiveness) and simultaneously sustainability (increasing energy efficiency, reducing losses/wastes and shorten Order to Delivery Time) of the Swedish manufacturing industry. The methodology is so called Holistic Simulation Optimisation (HSO) because unlike today's industrial practice that productivity, cost and sustainability are optimised separately, the framework proposed takes into account productivity, cost, and sustainability in a multi-level and multi-objective context. The HSO methodology is realised through the development of a software toolset that synergistically integrates Discrete Event Simulation with the sustainability and cost models that have been developed or extended by industrial companies with state-of-the-art multi-objective optimisation and data mining technologies. The potential benefits of using the HSO methodology on the efficiency of the production systems that are measurable and can be verified quantitatively are: 5-15% increase in productivity; 10-20% reduction in manufacturing lead time; reduction in environmental wastes, in terms of energy use and other forms of losses (10-20%). The paper will present how these estimations are based on the case studies conducted in Swedish automotive industry.

  • 420.
    Ng, Amos
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Persson, Jacob
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Urenda Moris, Matias
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Introducing Simulation-based Optimization for Production Systems Design to Industry: the FACTS Game2008In: Proceedings of the 18th International Conference on Flexible Automation and Intelligent Manufacturing: FAIM 2008, June 30th – July 2nd, 2008 University of Skövde, Sweden, Skövde: University of Skövde , 2008, p. 1359-1372Conference paper (Refereed)
  • 421.
    Ng, Amos
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Grimm, Henrik
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Svensson, Jacob
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Multi-Objective Simulation Optimization and Significant Dominance for Comparing Production Control Mechanisms2008In: Proceedings of the 18th International Conference on Flexible Automation and Intelligent Manufacturing, Skövde, Sweden, 2008, Skövde: University of Skövde , 2008Conference paper (Refereed)
  • 422.
    Ng, Amos
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Urenda Moris, Matias
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Jägstam, Mats
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Svensson, Jacob
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    An Internet-Enabled Tool for Multi-Objective Simulation Optimization2009In: OPTIMA 2009: VIII Congreso Chileno de Investigacion Operativa, 2009Conference paper (Refereed)
  • 423.
    Nilsson, Fredrik
    et al.
    Lund University.
    Karlsson, Krister
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Aryasetiawan, Ferdi
    Lund University.
    Dynamically screened Coulomb interaction in the parent compounds of hole-doped cuprates: Trends and exceptions2019In: Physical Review B. Condensed Matter and Materials Physics, ISSN 1098-0121, E-ISSN 1550-235X, Vol. 99, no 7, p. 1-9, article id 075135Article in journal (Refereed)
    Abstract [en]

    Although cuprate high-temperature superconductors were discovered already in 1986 the origin of the pairing mechanism remains elusive. While the doped compounds are superconducting with high transition temperatures T-c, the undoped compounds are insulating due to the strong effective Coulomb interaction between the Cu 3d holes. We investigate the dependence of the maximum superconducting transition temperature T-cmax on the on-site effective Coulomb interaction U using the constrained random-phase approximation. We focus on the commonly used one-band model of the cuprates, including only the antibonding combination of the Cu d(x2-y2) and O p(x) and p(y) orbitals and find a screening-dependent trend between the static value of U and T-cmax for the parent compounds of a large number of hole-doped cuprates. Our results suggest that superconductivity may be favored by a large on-site Coulomb repulsion. We analyze both the trend in the static value of U and its frequency dependence in detail and, by comparing our results to other works, speculate on the mechanisms behind the trend.

  • 424.
    Nilsson, Pernilla
    et al.
    Högskolan i Halmstad.
    Johansson, Hans
    University of Skövde, School of Technology and Society.
    Högberg, Dan
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Arén, Björn
    Örebro universitet.
    Söderström, Eva
    University of Skövde, School of Humanities and Informatics.
    Chibba, Aron
    Högskolan i Halmstad.
    Distribuerad case-metodik i ingenjörsutbildningen2009In: Den 2:a Utvecklingskonferensen för Sveriges ingenjörsutbildningar, Lunds Tekniska Högskola, Genombrottet , 2009, p. 71-73Conference paper (Other academic)
    Abstract [en]

    This paper is based on a project in which an academic developer worked as a critical friend for a group of engineering in order to stimulate their collaboration and their reflection on their own teaching and learning as a way of developing their scholarship of teaching. The project was built on collaboration between three different universities, Halmstad, Örebro and Skövde and reports on how teachers, as well as the students collaborative learning experiences.

  • 425.
    Nourmohammadi, Amir
    et al.
    Faculty of Industrial & Systems Engineering, Tarbiat Modares University, Tehran, Iran.
    Eskandari, Hamidreza
    Iran Management & Technology Development Center, Tarbiat Modares University, Tehran, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Design of stochastic assembly lines considering line balancing and part feeding with supermarkets2019In: Engineering optimization (Print), ISSN 0305-215X, E-ISSN 1029-0273, Vol. 51, no 1, p. 63-83Article in journal (Refereed)
    Abstract [en]

    This article aims to address the assembly line balancing problem (ALBP) and supermarket location problem (SLP) as two long-term interrelated decision problems considering the stochastic nature of the task times and demands. These problems arise in real-world assembly lines during the strategic decision-making phase of configuring new assembly lines from both line balancing and part-feeding (PF) aspects. A hierarchical mathematical programming model is developed, in which the first level resolves the stochastic ALBP by minimizing the workstation numbers and the second level deals with the stochastic SLP while optimizing the PF shipment, inventory and installation costs. The results of case data from an automotive parts manufacturer and a set of standard test problems verified that the proposed model can optimize the configuration of assembly lines considering both ALBP and SLP performance measures. This study also validates the effect of the stochastic ALBP on the resulting SLP solutions.

  • 426.
    Nourmohammadi, Amir
    et al.
    Tarbiat Modares University, Tehran, Iran.
    Eskandari, Hamidreza
    Tarbiat Modares University, Tehran, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Aghdasi, Mohammad
    Tarbiat Modares University, Tehran, Iran.
    A mathematical model for supermarket location problem with stochastic station demands2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 6p. 444-449Article in journal (Refereed)
    Abstract [en]

    This paper aims to investigate the effect of station demands variations on supermarket location problem (SLP). This problem arises in the real-world assembly line part feeding (PF) context where supermarkets are used as the intermediate storage areas for stations. To this purpose a stochastic SLP model is developed to optimize the total cost of PF in terms of shipment, inventory and installation costs. The computational results over a real case as well as different test instances verify that the station demands variation has an effect on the SLP solutions.

  • 427.
    Nourmohammadi, Amir
    et al.
    Tarbiat Modares University, Tehran, Iran.
    Eskandari, Hamidreza
    Tarbiat Modares University, Tehran, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ranjbar Bourani, Mehdi
    University of Science & Technology of Mazandaran, Behshahr, Iran.
    An integrated model for cost-oriented assembly line balancing and parts feeding with supermarkets2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 5p. 381-385Article in journal (Refereed)
    Abstract [en]

    This paper aims to deal with assembly line design from both line balancing and parts feeding (PF) aspects as two-interrelated decision problems while supermarkets are used. These problems arise in the real-world assembly lines (ALs) where decision makers are planning to simultaneously determine the optimal number of stations and the optimal number of supermarkets so that the total installation costs of ALs including line balancing and PF costs are minimized. To this purpose an integrated mathematical model is proposed and its performance is tested through solving a number of benchmark problems and a real case taken from industry.

  • 428.
    Nourmohammadi, Amir
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Fathi, Masood
    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.
    Choosing efficient meta-heuristics to solve the assembly line balancing problem: A landscape analysis approach2019In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 81, p. 1248-1253Article in journal (Refereed)
    Abstract [en]

    It is widely known that the assembly line balancing problem (ALBP) is an NP-hard optimization problem. Although different meta-heuristics have been proposed for solving this problem so far, there is no convincing support that what type of algorithms can perform more efficiently than the others. Thus, using some statistical measures, the landscape of the simple ALBP is studied for the first time in the literature. The results indicate a flat landscape for the problem where the local optima are uniformly scattered over the search space. Accordingly, the efficiency of population-based algorithms in addressing the considered problem is statistically validated.

  • 429.
    Nourmohammadi, Amir
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ruiz Zúñiga, Enrique
    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.
    A Genetic Algorithm for Bi-Objective Assembly Line Balancing Problem2019In: Advances in Manufacturing Technology XXXIII: Proceedings of the 17th International Conference on Manufacturing Research, incorporating the 34th National Conference on Manufacturing Research, September 10–12, 2019, Queen’s University Belfast, UK / [ed] Yan Jin, Mark Price, Amsterdam: IOS Press, 2019, Vol. 9, p. 519-524Conference paper (Refereed)
    Abstract [en]

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

  • 430.
    Nourmohammadi, Amir
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Zandieh, Mostafa
    Department of Industrial Management, Management and Accounting Faculty, SBU, G.C., Tehran, Iran.
    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.
    A water-flow like algorithm for solving U-shaped assembly line balancing problems2019In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 129824-129833Article in journal (Refereed)
    Abstract [en]

    The problem of assigning assembly tasks to the stations arranged along a material handling device is known as assembly line balancing. This paper aims to address the U-shaped assembly line balancing problem (UALBP) which arises when a U-shaped assembly line has to be configured. It is widely known that this problem is NP-hard. Accordingly, different meta-heuristics based on a single solution (such as Simulated Annealing) or a population of solutions (such as Genetic Algorithms) have been proposed in the literature. Meanwhile, it has been argued that either of these meta-heuristics with a fixed number of solutions cannot maintain efficient search progress and thus can lead to premature convergence. Thus, this study aims at adopting a novel meta-heuristic algorithm with dynamic population sizes, namely Water Flow-like Algorithm (WFA), inspired by the behaviour of water flows in nature, to address the UALBP. The line efficiency and variation of workload are considered as the primary and the secondary objective, to be optimized, respectively. To verify the efficiency and robustness of the proposed WFA, a real case study taken from an automobile manufacturer as well as a set of standard problems are solved and the results compared with the existing approaches in the literature. The computational results demonstrate the superiority of the WFA, particularly in addressing medium to large-sized problems.

  • 431.
    Olofsson, Jakob
    et al.
    Department of Materials and Manufacturing – Casting, Jönköping University, School of Engineering, Jönköping, Sweden.
    Salomonsson, Kent
    Department of Product Development, Jönköping University, School of Engineering, Jönköping, Sweden.
    Johansson, Joel
    Department of Product Development, Jönköping University, School of Engineering, Jönköping, Sweden.
    Amouzgar, Kaveh
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    A methodology for microstructure-based structural optimization of cast and injection moulded parts using knowledge-based design automation2017In: Advances in Engineering Software, ISSN 0965-9978, E-ISSN 1873-5339, Vol. 109, p. 44-52Article in journal (Refereed)
    Abstract [en]

    The local material behaviour of cast metal and injection moulded parts is highly related to the geometrical design of the part as well as to a large number of process parameters. In order to use structural optimization methods to find the geometry that gives the best possible performance, both the geometry and the effect of the production process on the local material behaviour thus has to be considered. In this work, a multidisciplinary methodology to consider local microstructure-based material behaviour in optimizations of the design of engineering structures is presented. By adopting a knowledge based industrial product realisation perspective combined with a previously presented simulation strategy for microstructure-based material behaviour in Finite Element Analyses (FEA), the methodology integrates Computer Aided Design (CAD), casting and injection moulding simulations, FEA, design automation and a multi-objective optimization scheme into a novel structural optimization method for cast metal and injection moulded polymeric parts. The different concepts and modules in the methodology are described, their implementation into a prototype software is outlined, and the application and relevance of the methodology is discussed. 

  • 432.
    Ore, Fredrik
    et al.
    Mälardalen University, Eskilstuna / Scania CV AB, Södertälje.
    Hanson, Lars
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Chalmers University of Technology / Scania CV AB, Södertälje.
    Delfs, Niclas
    Fraunhofer-Chalmers Centre, Göteborg.
    Wiktorsson, Magnus
    Mälardalen University, Eskilstuna.
    Human Industrial Robot Collaboration – development and application of simulation software2015In: International Journal of Human Factors Modelling and Simulation, ISSN 1742-5557, Vol. 5, no 2, p. 164-185Article, review/survey (Refereed)
    Abstract [en]

    Human industrial robot collaboration (HIRC) aims to combine the benefits of industrial robots with humans in production environments. This is a growing research field where most work focuses on the safety aspects, while little research is performed on simulation and visualisation. The aim of this paper is to present a demonstrator software for simulation, visualisation and evaluation of human industrial robot collaboration.

    Two simulation software products were combined to reach this goal. The new tool was then applied to two industrial assembly cases where productivity and biomechanical loads on humans were calculated. The resulting demonstrator software simulates and visualises human industrial robot collaboration. The quantitative output from the simulation makes it possible to compare HIRC, manual and robotic assembly stations in terms of productivity and ergonomics.

  • 433.
    Ore, Fredrik
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Eskilstuna, Sweden / Scania CV AB, Global Industrial Development, Södertälje, Sweden.
    Hansson, Lars
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Scania CV AB, Global Industrial Development, Södertälje, Sweden / Chalmers University of Technology, Department of Product and Production Development, Gothenburg, Sweden.
    Wiktorsson, Magnus
    Mälardalen University, School of Innovation, Design and Engineering, Eskilstuna, Sweden.
    Method for design of human-industrial robot collaboration workstations2017In: Procedia Manufacturing, E-ISSN 2351-9789, Vol. 11, p. 4-12Article in journal (Refereed)
    Abstract [en]

    In order to fully utilise a 3D simulation software capable of evaluating hand-guided human-industrial robot collaborative (HIRC) work tasks, there is a need of a HIRC design process for early production development stages. This paper proposes a HIRC design method that uses the possibilities of the demonstrator software in the HIRC workstation design process. The method is based on Pahl and Beitz's engineering design method; it interprets all their phases and activities into HIRC design-specific ones.

  • 434.
    Ore, Fredrik
    et al.
    School of Innovation, Design and Engineering, Mälardalen University, Eskilstuna / Scania CV AB, Global Industrial Development, Södertälje, Sweden.
    Vemula, Bhanoday
    School of Innovation, Design and Engineering, Mälardalen University, Eskilstuna.
    Hanson, Lars
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Scania CV AB, Global Industrial Development, Södertälje / Department of Industrial and Materials Science, Chalmers University of Technology, Göteborg.
    Wiktorsson, Magnus
    School of Innovation, Design and Engineering, Mälardalen University, Eskilstuna.
    Fagerström, Björn
    School of Innovation, Design and Engineering, Mälardalen University, Eskilstuna.
    Simulation methodology for performance and safety evaluationof human–industrial robot collaboration workstation design2019In: International Journal of Intelligent Robotics and Applications, ISSN 2366-5971, Vol. 3, no 3, p. 269-282Article in journal (Refereed)
    Abstract [en]

    There is a strong interest in the scope of human–industrial robot collaboration (HIRC) in manufacturing industry for greater flexibility and productivity. However, HIRC in manufacturing is still in its infancy; industrial practitioners have many apprehensions and uncertainties concerning the system’s performance and human operators’ safety. Therefore, there is a need for investigations into design processes and methods to make sure the designed HIRC workstations successfully meet design guidelines on system performance, human safety and ergonomics for practical industrial applications. This research proposes a HIRC workstation design process. The novelty of this design process is the methodology to evaluate the HIRC workstation design alternatives by considering both performance and safety characteristics through computer-based simulations. As a proof of concept, the proposed HIRC design process is applied on an industrial manufacturing case from a heavy-vehicle manufacturing company.

  • 435.
    Ore, Fredrik
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Eskilstuna, Sweden / Scania CV AB, Global Industrial Development, Södertälje, Sweden.
    Vemula, Bhanoday Reddy
    Mälardalen University, School of Innovation, Design and Engineering, Eskilstuna, Sweden.
    Hanson, Lars
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Scania CV AB, Global Industrial Development, Södertälje, Sweden / Chalmers University of Technology, Product and Production Development, Göteborg, Sweden.
    Wiktorsson, Magnus
    Mälardalen University, School of Innovation, Design and Engineering, Eskilstuna, Sweden.
    Human - Industrial Robot Collaboration: Application of simulation software for workstation optimisation2016In: 6th CIRP Conference on Assembly Technologies and Systems (CATS) / [ed] Rikard Söderberg, Elsevier, 2016, Vol. 44, p. 181-186Conference paper (Refereed)
    Abstract [en]

    The simulation possibilities of Human Industrial Robot Collaboration (HIRC) are limited in commercial software and published research. In order to meet this a demonstrator software has been developed. This paper presents the combination of the quantitative output from the software (measuring operation time and biomechanical load) together with existing optimisation techniques used to design the optimal HIRC workstation. An industrial case is used as an example where the optimal geometric handover position between robot and human is found. From the simulation software metamodels were created in order to represent the investigated workstation. The model was used in a multi-objective optimisation problem and resulted in a trade-off chart between operation time and biomechanical load. The result shows one example of the possibilities to combine the quantitative results from the simulation with optimisation in order to get the best solution to a HIRC design problem. (C) 2016 The Authors. Published by Elsevier B.V.

  • 436.
    Oscarsson, Jan
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Jeusfeld, Manfred A.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Jenefeldt, Anders
    Volvo Cars Corporation, Skövde, Sweden.
    Towards Virtual Confidence - Extended Product Lifecycle Management2016In: Product Lifecycle Management in the Era of Internet of Things: 12th IFIP WG 5.1 International Conference, PLM 2015, Doha, Qatar, October 19-21, 2015, Revised Selected Papers / [ed] Abdelaziz Bouras, Benoit Eynard, Sebti Foufou & Klaus-Dieter Thoben, Springer, 2016, Vol. 467, p. 708-717Chapter in book (Refereed)
    Abstract [en]

    Product lifecycle management (PLM) systems maintain amongst others the specifications and designs of product, process and resource artefacts and thus serve as the basis for realizing the concept of Virtual Manufacturing, and play a vital role in shortening the leadtimes for the engineering processes. Design of new products requires numerous experiments and test-runs of new facilities that delays the product release and causes high costs if performed in the real world. Virtualization promises to reduce these costs by simulating the reality. However, the results of the simulation must predict the real results to be useful. This is called virtual confidence. We propose a knowledge base approach to capture and maintain the virtual confidence in simulation results. To do so, the provenance of results of real, experimental and simulated processes are recorded and linked via confirmation objects.

  • 437.
    Pehrsson, Leif
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Manufacturing management and decision support using simulation-based multi-objective optimisation2013Doctoral thesis, monograph (Other academic)
    Abstract [en]

    A majority of the established automotive manufacturers are under severe competitive pressure and their long term economic sustainability is threatened. In particular the transformation towards more CO2-efficient energy sources is a huge financial burden for an already investment capital intensive industry. In addition existing operations urgently need rapid improvement and even more critical is the development of highly productive, efficient and sustainable manufacturing solutions for new and updated products. Simultaneously, a number of severe drawbacks with current improvement methods for industrial production systems have been identified. In summary, variation is not considered sufficient with current analysis methods, tools used are insufficient for revealing enough knowledge to support decisions, procedures for finding optimal solutions are not considered, and information about bottlenecks is often required, but no accurate methods for the identification of bottlenecks are used in practice, because they do not normally generate any improvement actions. Current methods follow a trial-and-error pattern instead of a proactive approach. Decisions are often made directly on the basis of raw static historical data without an awareness of optimal alternatives and their effects. These issues could most likely lead to inadequate production solutions, low effectiveness, and high costs, resulting in poor competitiveness. In order to address the shortcomings of existing methods, a methodology and framework for manufacturing management decision support using simulation-based multi-objective optimisation is proposed. The framework incorporates modelling and the optimisation of production systems, costs, and sustainability. Decision support is created through the extraction of knowledge from optimised data. A novel method and algorithm for the detection of constraints and bottlenecks is proposed as part of the framework. This enables optimal improvement activities with ranking in order of importance can be sought. The new method can achieve a higher improvement rate, when applied to industrial improvement situations, compared to the well-established shifting bottleneck technique. A number of “laboratory” experiments and real-world industrial applications have been conducted in order to explore, develop, and verify the proposed framework. The identified gaps can be addressed with the proposed methodology. By using simulation-based methods, stochastic behaviour and variability is taken into account and knowledge for the creation of decision support is gathered through post-optimality analysis. Several conflicting objectives can be considered simultaneously through the application of multi-objective optimisation, while objectives related to running cost, investments and other sustainability parameters can be included through the use of the new cost and sustainability models introduced. Experiments and tests have been undertaken and have shown that the proposed framework can assist the creation of manufacturing management decision support and that such a methodology can contribute significantly to regaining profitability when applied within the automotive industry. It can be concluded that a proof-of-concept has been rigorously established for the application of the proposed framework on real-world industrial decision-making, in a manufacturing management context.

  • 438.
    Pehrsson, Leif
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Research and Technology Development, Engine Manufacturing Engineering, Volvo Car Group.
    Frantzén, Marcus
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Aslam, Tehseen
    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.
    Aggregated line modeling for simulation and optimization of manufacturing systems2015In: 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, Piscataway, NJ, USA: IEEE Press, 2015, p. 3632-3643Conference paper (Refereed)
    Abstract [en]

    In conceptual analysis of higher level manufacturing systems, for instance, when the constraint on system level is sought, it may not be very practical to use detailed simulation models. Developing detailed models on supply chain level or plant wide level may be very time consuming and might also be computationally costly to execute, especially if optimization techniques are to be applied. Aggregation techniques, simplifying a detailed system into fewer objects, can be an effective method to reduce the required computational resources and to shorten the development time. An aggregated model can be used to identify the main system constraints, dimensioning inter-line buffers, and focus development activities on the critical issues from a system performance perspective. In this paper a novel line aggregation technique suitable for manufacturing systems optimization is proposed, analyzed and tested in order to establish a proof of concept while demonstrating the potential of the technique.

  • 439.
    Pehrsson, Leif
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Volvo Car Corporation, Gothenburg, Sweden.
    Karlsson, Ingemar
    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.
    Towards Automated Multi-Objective Rule Extraction2016In: Proceedings of the 2016 European Simulation and Modelling Conference / [ed] José Évora-Gómez & José Juan Hernandéz-Cabrera, EUROSIS - The European Multidisciplinary Society for Modelling and Simulation Technology , 2016, p. 64-68Conference paper (Refereed)
  • 440.
    Pehrsson, Leif
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Volvo Car Corporation, Gothenburg, Sweden.
    Lidberg, Simon
    Volvo Car Corporation, Gothenburg, Sweden.
    Frantzén, Marcus
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Aslam, Tehseen
    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.
    Aggregated Discrete Event Modelling for Simulation and Optimisation of Manufacturing Systems2014In: Industrial Simulation Conference, Skövde, June 11-13, 2014, Eurosis, 2014, 2014, p. 83-90Conference paper (Refereed)
    Abstract [en]

    In many simulation studies for factory analysis, for example, to locate the constraint of an entire factory that consists of multiple production lines, it may not be effective to put every process detail into a single model. Firstly, to develop such a factory-wide model would be very time-consuming. Secondly, it can be very computational costly to run the model, especially if simulation-based optimisation is applied to find the optimal setting from such a complex model that possesses all the details of the processes. In this regard, aggregation, with which multiple process steps are aggregated into some simpler simulation objects, is an effective method to reduce both the development and computational times. On one hand, based on the initial analysis, the simulation expert can pinpoint the sub-system that restrains the performance of the entire factory and decide if a more detailed model is needed. On the other hand, interline buffers/storages can be readily optimised by using such an aggregated model. Through an application study with data from a real-world factory, this paper introduces a novel aggregation method and illustrates the potential of the abovesaid concepts.

  • 441.
    Pehrsson, Leif
    et al.
    Volvo Car Corporation, Gothenburg, Sweden.
    Ng, Amos H. C.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Decision-making in conceptual AGV systems design using simulation-based optimization2013In: Proceedings of Industrial Simulation Conference, May 22-24, Ghent, Belgium, 2013, p. 171-176Conference paper (Refereed)
  • 442.
    Pehrsson, Leif
    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.
    Bernedixen, Jacob
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Automatic identification of constraints and improvement actions in production systems using multi-objective optimization and post-optimality analysis2016In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 39, p. 24-37Article in journal (Refereed)
    Abstract [en]

    Manufacturing companies are operating in a severely competitive global market, which renders an urgent need for them to explore new methods to enhance the performance of their production systems in order to retain their competitiveness. Regarding the performance of a production system, it is not sufficient simply to detect which operations to improve, but it is imperative to pinpoint the right actions in the right order to avoid sub-optimizations and wastes in time and expense. Therefore, a more accurate and efficient method for supporting system improvement decisions is greatly needed in manufacturing systems management. Based on research in combining simulation-based multi-objective optimization and post-optimality analysis methods for production systems design and analysis, a novel method for the automatic identification of bottlenecks and improvement actions, so-called Simulation-based Constraint Identification (SCI), is proposed in this paper. The essence of the SCI method is the application of simulation-based multi-objective optimization with the conflicting objectives to maximize the throughput and minimize the number of required improvement actions simultaneously. By using post-optimality analysis to process the generated optimization dataset, the exact improvement actions needed to attain a certain level of performance of the production line are automatically put into a rank order. In other words, when compared to other existing approaches in bottleneck detection, the key novelty of combining multi-objective optimization and post-optimality analysis is to make SCI capable of accurately identifying a rank order for the required levels of improvement for a large number of system parameters which impede the performance of the entire system, in a single optimization run. At the same time, since SCI is basically built a top a simulation-based optimization approach, it is capable of handling large-scale, real-world system models with complicated process characteristics. Apart from introducing such a method, this paper provides some detailed validation results from applying SCI both in hypothetical examples that can easily be replicated as well as a complex, real-world industrial improvement project. The promising results compared to other existing bottleneck detection methods have demonstrated that SCI can provide valuable higher-level information to support confident decision-making in production systems improvement.

  • 443.
    Pehrsson, Leif
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos H. C.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Bernedixen, Jacob
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Multi-objective production system optimisation including investment and running costs2011In: Proceedings of the 4th Swedish Production Symposium, SPS11, May 3-5, Lund, Sweden, Lund, 2011Conference paper (Refereed)
  • 444.
    Pehrsson, Leif
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos H. C.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Bernedixen, Jacob
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Multi-objective Production Systems Optimisation with Investment and Running Cost2011In: Multi-objective Evolutionary Optimisation for Product Design and Manufacturing / [ed] Lihui Wang, Amos H. C. Ng, Kalyanmoy Deb, Springer London, 2011, p. 431-453Chapter in book (Refereed)
    Abstract [en]

    In recent years simulation-based multi-objective optimisation (SMO) of production systems targeting e.g., throughput, buffers and work-in-process (WIP) has been proven to be a very promising concept. In combination with post-optimality analysis, the concept has the potential of creating a foundation for decision support. This chapter will explore the possibility to expand the concept of introducing optimisation of production system cost aspects such as investments and running cost. A method with a procedure for industrial implementation is presented, including functions for running cost estimation and investment combination optimisation. The potential of applying SMO and postoptimality analysis, taking into account both productivity and financial factors for decision-making support, has been explored and proven to be very beneficial for this kind of industrial application. Evaluating several combined minor improvements with the help of SMO has opened the opportunity to identify a set of solutions (designs) with great financial improvement, which are not feasible to be explored by using current industrial procedures.

     

  • 445.
    Pehrsson, Leif
    et al.
    Volvo Car Corporation, Gothenburg, Sweden.
    Ng, Amos H. C.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Bernedixen, Jacob
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Stockton, David
    De Montfort University, Leicester, United Kingdom.
    Sectioned Walking Worker Lines with Loop Balancing2013Conference paper (Refereed)
  • 446.
    Pehrsson, Leif
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos H. C.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Stockton, David
    Centre for Manufacturing, De Montfort University, Leicester, UK.
    Industrial cost modelling and multi-objective optimisation for decision support in production systems development2013In: Computers & industrial engineering, ISSN 0360-8352, E-ISSN 1879-0550, Vol. 66, no 4, p. 1036-1048Article in journal (Refereed)
    Abstract [en]

    Recent developments in cost modelling, simulation-based multi-objective optimisation, and post-optimality analysis have enabled the integration of costing data and cost estimation into a new methodology for supporting economically sound decision-making in manufacturing enterprises. Within this methodology, the combination of production engineering and financial data with multi-objective optimisation and post-optimality analysis has been proven to provide the essential information to facilitate knowledge-driven decision-making in real-world production systems development. The focus of this paper is to present the incremental cost modelling technique specifically designed for the integration with discrete-event simulation models and multi-objective optimisation within this methodology. A complete example, using the simulation model and data modified from a previous real-world case study, is provided in this paper to illustrate how the methodology and cost modelling are applied for the optimal investment decision support. (C) 2013 Elsevier Ltd. All rights reserved.

  • 447.
    Pehrsson, Leif
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre. Volvo Car Corporation, Gothenburg, Sweden.
    Ng, Amos. H.C.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    An Applied Framework for simulation-based multi-objective optimisation within production system development2011In: Proceedings of the 9th Industrial Simulation Conference, Eurosis , 2011, p. 121-128Conference paper (Refereed)
    Abstract [en]

    A method and a framework for the application of Simulation-based Multi-objective Optimisation (SMO) has been developed in order to enhance the prerequisites for decision-making within design and re-configuration of production systems. This kind of decisions often tends to be based on financial information rather than the type of production system parameters to be found in traditional simulation models. Therefore, to combine traditional parameters with new financial and sustainability parameters can be very beneficial for supporting industrial decision-making. The framework has been applied in a number of case studies involving a range of production system issues both within component production and assembly operations. Several types of issues have been explored involving analysis of system behaviour, optimisation of sustainability parameters, in the form of energy consumption aggregated to energy cost, and optimisation of financial parameters in combination with traditional production system metrics. The case studies have adequately proven and verified that the application of SMO, especially including financial functions and objectives, can be very valuable for practical industrial applications.

  • 448.
    Prasoon, Ruchir
    et al.
    Department of Mechanical Engineering, Indian Institute of Technology, Kharagpur, 721302, W Bengal, India.
    Das, Devashish
    Department of Mechanical Engineering, Indian Institute of Technology, Kharagpur, 721302, W Bengal, India.
    Tiwari, Manoj Kumar
    Department of Industrial Engineering, Indian Institute of Technology, Kharagpur, 721302, W Bengal, India.
    Wang, Lihui
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    An algorithm portfolio approach to reconfigurable set-up planning2011In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 24, no 8, p. 756-768Article in journal (Refereed)
    Abstract [en]

    This article discusses an algorithm portfolio approach to find optimal set-up plans in a dynamic shop floor environment where flexibility and promptness of the decision process is critical along with best possible utilisation of the available resources. An evolutionary algorithm based reconfigurable set-up planning approach is presented where the final set-up plan is determined in two steps: primitive set-up planning through feature grouping and reconfigurable set-up merging based on real time information from the scheduling system. The tendency of single algorithm approach to converge to sub-optimal solutions was countered by using portfolios of genetic algorithm and its three variants: Genetic Algorithm with Chromosome Differentiation, Sexual Genetic Algorithm and a modified version of Age Genetic Algorithm. Best performing portfolios selected after exhaustive experimentation showed dramatic computational improvements in achieving the optimal solution validating the appropriateness and effectiveness of algorithm portfolio approach.

  • 449.
    Rambusch, Jana
    et al.
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Virtual Systems Research Centre.
    Susi, Tarja
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Serious Learning while Having Fun2010In: Kognition und Technologie im kooperativen Lernen: Vom Wissenstransfer zur Knowledge Creation, Göttingen: Vandenhoeck & Ruprecht, 2010, p. 77-90Chapter in book (Refereed)
    Abstract [en]

    In this paper we consider learning in the context of computer games, in terms of socio-cultural theories on learning and cognition. We emphasise on the tools involved in players’ learning activities, such as the use of »social tools«, and their role in the learning situation. Integrating (parts of) the computer game area with socio-cultural learning theories can prove beneficial for a more balanced understanding of learning in computer (game) environments. As a step in this direction, this paper discusses a case study of Counter-strike players and their learning from a cognitive science perspective.

  • 450. Rexfelt, O
    et al.
    Hiort af Ornäs, Viktor
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Funktionsförsäljning till privatkonsumenter: Resonemang kring fyra funktionserbjudanden2006Report (Other academic)
6789101112 401 - 450 of 658
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