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  • 1.
    Bernedixen, Jacob
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Engineering Science.
    Ng, Amos H. C.
    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.
    On the convergence of stochastic simulation-based multi-objective optimization for bottleneck identificationIn: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588XArticle in journal (Refereed)
    Abstract [en]

    By innovatively formulating a bottleneck identication problem into a bi-objective optimization,simulation-based multi-objective optimization (SMO) can be eectively used as a new method for gen-eral production systems improvement. In a single optimization run, all attainable, maximum throughputlevels of the system can be sought through various optimal combinations of improvement changes ofthe resources. Additionally, the post-optimality frequency analysis on the Pareto-optimal solutions cangenerate a rank order of the attributes of the resources required to achieve the target throughput levels.Observing that existing research mainly put emphasis on measuring the convergence of the optimizationin the objective space, leaving no information on when the solutions in the decision space have convergedand stabilized, this paper represents the rst eort in increasing the knowledge about the convergence ofSMO for the rank ordering in the context of bottleneck analysis. By customizing the Spearman's footruledistance and Kendall's tau, this paper presents how these metrics can be used eectively to provide thedesired visual aid in determining the convergence of bottleneck ranking, hence can assist the user todetermine correctly the terminating condition of the optimization process. It illustrates and evaluatesthe convergence of the SMO for bottleneck analysis on a set of scalable benchmark models as well as twoindustrial simulation models. The results have shed promising direction of applying these new metrics tocomplex, real-world applications.

  • 2.
    Hanson, Robin
    et al.
    Chalmers University of Technology.
    Brolin, Anna
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    A comparison of kitting and continuous supply in in-plant materials supply2013In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 51, no 4, p. 979-992Article in journal (Refereed)
    Abstract [en]

    In the context of in-plant materials supply, the materials feeding principle of kitting is often discussed as an alternative to the more common continuous supply (also known as line stocking). However, there are few detailed studies describing the relative effects of kitting and continuous supply. The current paper identifies the relative effects of kitting and continuous supply, and provides insight into how these effects arise. The paper draws on empirical data from two case studies in the Swedish automotive assembly industry. In each of the cases, continuous supply has been replaced by kitting, enabling comparison of kitting and continuous supply in the same production environment. The performance areas studied include man-hour consumption, product quality, flexibility, inventory levels, and space requirements. Interviews with production engineers, assemblers, and operators responsible for kit preparation at each company contribute to a broad yet detailed view of the relative effects of the two materials feeding principles.

  • 3.
    Moore, P. R.
    et al.
    De Montfort Univ, Mechatron Res Grp, Leicester LE1 9BH, Leics, England.
    Ng, Amos
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Yeo, S. H.
    De Montfort Univ, Mechatron Res Grp, Leicester LE1 9BH, Leics, England.
    Sundberg, Martin
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Wong, C. B.
    De Montfort Univ, Mechatron Res Grp, Leicester LE1 9BH, Leics, England.
    De Vin, Leo
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Advanced machine service support using Internet-enabled three-dimensional-based virtual engineering2008In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 46, no 15, p. 4215-4235Article in journal (Refereed)
    Abstract [en]

    In the era of globalization, one of the key factors for manufacturing machine builders/suppliers to remain competitive is their capability to provide cost-effective and comprehensive machine service and maintenance for their clients at anytime, anywhere. Previous research has highlighted the role of virtual engineering tools in the design and development life cycle of manufacturing machinery systems. Virtual engineering models created during the development phase can potentially be used to provide valuable functions for many other tasks during the operational phase, including service and maintenance support. This paper introduces an innovative Internet-enabled three-dimensional-based virtual engineering framework that can be used for such purposes. Specifically, it addresses a system architecture that is designed to facilitate the tight integration between virtual engineering tools and a set of Internet-based reconfigurable modular maintenance supporting tools. This system architecture has been verified by implementations using different toolsets atop of various Internet technologies (e.g. XML Web services and LabView's Datasocket). Implementation details and successful industrial-based test cases are also provided in this paper.

  • 4.
    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.

  • 5.
    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.

  • 6.
    Wang, Lihui
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Keshavarzmanesh, Shadi
    Univ Western Ontario, Dept Mech & Mat Engn, London, ON, Canada .
    Feng, Hsi-Yung
    Univ British Columbia, Dept Mech Engn, Vancouver, BC V6T 1W5, Canada.
    A function block based approach for increasing adaptability of assembly planning and control2011In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 49, no 16, p. 4903-4924Article in journal (Refereed)
    Abstract [en]

    Today's market turbulences cause frequent changes in manufacturing environments. Products diversity, small batch sizes and short life cycles have increased production uncertainties and created a highly dynamic shop floor environment. One essential requirement of such an environment is an adaptive planning and control system that is sufficiently agile to respond to the variety of production requirements and enable easy system reconfiguration at run-time. When developing a product, assembly is a key area that impacts the manufacturing system's responsiveness to the changes. In this research, a framework and a new methodology are introduced to increase the adaptability and autonomy of job-shop assembly process planning and control using function blocks (FBs). A function block is a reusable functional module with an explicit event-driven model, and provides for data flow and finite state automata based control. Event-driven and FB-enabled decision-making is unique in adaptive assembly planning and control. It is explained through an example of a two-robot assembly work cell, where the result of the adaptive planning is wrapped in FBs for execution. The proposed approach has been implemented and simulated using Matlab Simulink in the case study. The simulation demonstrates how this approach would increase the adaptability and responsiveness to changes that may occur regularly in dynamic job-shop assembly operations.

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