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  • 1.
    Adamson, Göran
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Wang, Lihui
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Department of Production Engineering, Royal Institute of Technology, Stockholm, Sweden.
    Moore, Philip
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Feature-based Function Block Control Framework for Manufacturing Equipment in Cloud Environments2018In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 57, no 12, p. 3954-3974Article in journal (Refereed)
    Abstract [en]

    The ability to adaptively control manufacturing equipment in cloud environments is becoming increasingly more important. Industry 4.0, supported by Cyber Physical Systems and the concept of on-demand, scalable and pay-for-usage resource-sharing in cloud environments offers many promises regarding effective and flexible manufacturing. For implementing the concept of manufacturing services in a cloud environment, a cloud control approach for the sharing and control of networked manufacturing resources is required. This paper presents a cloud service-based control approach which has a product perspective and builds on the combination of event-driven IEC 61499 Function Blocks and product manufacturing features. Distributed control is realised through the use of a networked control structure of such Function Blocks as decision modules, enabling an adaptive run-time behaviour. The control approach has been developed and implemented as prototype systems for both local and distributed manufacturing scenarios, in both real and virtual applications. An application scenario is presented to demonstrate the applicability of the control approach. In this scenario, Assembly Feature-Function Blocks for adaptive control of robotic assembly tasks have been used.

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  • 2.
    Amouzgar, Kaveh
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Uppsala University.
    Nourmohammadi, Amir
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Uppsala University.
    Multi-objective optimisation of tool indexing problem: a mathematical model and a modified genetic algorithm2021In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 59, no 12, p. 3572-3590Article in journal (Refereed)
    Abstract [en]

    Machining process efficiencies can be improved by minimising the non-machining time, thereby resulting in short operation cycles. In automatic-machining centres, this is realised via optimum cutting tool allocation on turret-magazine indices – the “tool-indexing problem”. Extant literature simplifies TIP as a single-objective optimisation problem by considering minimisation of only the tool-indexing time. In contrast, this study aims to address the multi-objective optimisation tool indexing problem (MOOTIP) by identifying changes that must be made to current industrial settings as an additional objective. Furthermore, tool duplicates and lifespan have been considered. In addition, a novel mathematical model is proposed for solving MOOTIP. Given the complexity of the problem, the authors suggest the use of a modified strength Pareto evolutionary algorithm combined with a customised environment-selection mechanism. The proposed approach attained a uniform distribution of solutions to realise the above objectives. Additionally, a customised solution representation was developed along with corresponding genetic operators to ensure the feasibility of solutions obtained. Results obtained in this study demonstrate the realization of not only a significant (70%) reduction in non-machining time but also a set of tradeoff solutions for decision makers to manage their tools more efficiently compared to current practices. 

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  • 3.
    Goienetxea, Ainhoa
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Department of Engineering Science, Uppsala University, Sweden.
    Urenda Moris, Matías
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Department of Engineering Science, Uppsala University, Sweden.
    Bringing together Lean and simulation: a comprehensive review2020In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 58, no 1, p. 87-117Article, review/survey (Refereed)
    Abstract [en]

    Lean is and will still be one of the most popular management philosophies in the Industry 4.0 context and simulation is one of its key technologies. Many authors discuss about the benefits of combining Lean and simulation to better support decision makers in system design and improvement. However, there is a lack of reviews in the domain. Therefore, this paper presents a four-stage comprehensive review and analysis of existing literature on their combination. The aim is to identify the state of the art, existing methods and frameworks for combining Lean and simulation, while also identifying key research perspectives and challenges. The main trends identified are the increased interest in the combination of Lean and simulation in the Industry 4.0 context and in their combination with optimisation, Six Sigma, as well as sustainability. The number of articles in these areas is likely to continue to grow. On the other hand, we highlight six gaps found in the literature regarding the combination of Lean and simulation, which may induce new research opportunities. Existing technical, organisational, as well as people and culture related challenges on the combination of Lean and simulation are also discussed.

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  • 4.
    Hanson, Robin
    et al.
    Department of Technology Management and Economics, Chalmers University of Technology, Gothenburg, Sweden.
    Brolin, Anna
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre. Department of Mechanical and Manufacturing Engineering, Loughborough University, UK.
    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.

  • 5.
    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.

  • 6.
    Ng, Amos H. C.
    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.
    Syberfeldt, Anna
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    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.

  • 7.
    Ng, Amos H. C.
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Shaaban, Sabry
    Department of Strategy, ESC La Rochelle, La Rochelle, France.
    Bernedixen, Jacob
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    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.

  • 8.
    Nourmohammadi, Amir
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Faculty of Industrial & Systems Engineering, Tarbiat Modares University, Tehran, Iran.
    Eskandari, Hamidreza
    Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran / School of Management, Swansea University, UK.
    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.
    Integrated locating in-house logistics areas and transport vehicles selection problem in assembly lines2021In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 59, no 2, p. 598-616Article in journal (Refereed)
    Abstract [en]

    Decentralised in-house logistics areas, known as supermarkets, are widely used in the manufacturing industry for parts feeding to assembly lines. In contrary to the literature and inspired by observation in a real case, this study relaxes the assumption of using identical transport vehicles when deciding on the supermarkets’ location by considering the availability of different vehicles. In this regard, this study deals with the integrated supermarket location and transport vehicles selection problems (SLTVSP). A mixed-integer programming (MIP) model of the problem is developed. Due to the complexity of the problem, a hybrid genetic algorithm (GA) with variable neighborhood search (GA-VNS) is also proposed to address large-sized problems. The performance of GA-VNS is compared against the MIP, the basic GA, and simulated annealing (SA) algorithm. The computational results from the real case and a set of generated test problems show that GA-VNS provides a very good approximation of the MIP solutions at a much shorter computational time while outperforming the other compared algorithms. The analysis of the results reveals that it is beneficial to apply different transport vehicles rather than identical vehicles for SLTVSP.

  • 9.
    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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