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  • 1.
    Ayani, Mikel
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ganebäck, Maria
    Projektengagemang Industri & Energi Sverige AB, El & Automation, Skövde, Sweden.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Digital Twin: Applying emulation for machine reconditioning2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 243-248Article in journal (Refereed)
    Abstract [en]

    Old machine reconditioning projects extend the life length of machines with reduced investments, however they frequently involve complex challenges. Due to the lack of technical documentation and the fact that the machines are running in production, they can require a reverse engineering phase and extremely short commissioning times. Recently, emulation software has become a key tool to create Digital Twins and carry out virtual commissioning of new manufacturing systems, reducing the commissioning time and increasing its final quality. This paper presents an industrial application study in which an emulation model is used to support a reconditioning project and where the benefits gained in the working process are highlighted.

  • 2.
    Danielsson, Oscar
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Holm, Magnus
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Wang, Lihui
    KTH Royal Institue of Technology, Stockholm, Sweden.
    Operators perspective on augmented reality as a support tool in engine assembly2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 45-50Article in journal (Refereed)
    Abstract [en]

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

  • 3.
    Fathi, Masood
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ghobakhloo, Morteza
    University of Hormozgan, Bandar Abbas, Iran.
    Eskandari, Hamidreza
    Tarbiat Modares University, Tehran, Iran.
    An optimization model for material supply scheduling at mixed-model assembly lines2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 6p. 1258-1263Article in journal (Refereed)
    Abstract [en]

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

  • 4.
    Flores Garcia, Erik
    et al.
    Mälardalen University, Eskilstuna, Sweden.
    Ruiz Zúñiga, Enrique
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Bruch, Jessica
    Mälardalen University, Eskilstuna, Sweden.
    Urenda Moris, Matias
    Division of Industrial Engineering and Management, University of Uppsala, Uppsala, Sweden.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Simulation-based Optimization for Facility Layout Design in Conditions of High Uncertainty2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 334-339Article in journal (Refereed)
    Abstract [en]

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

  • 5.
    Gandhi, Kanika
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Schmidt, Bernard
    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 data mining based decision support in manufacturing maintenance2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 261-265Article in journal (Refereed)
    Abstract [en]

    The current work presents a decision support system architecture for evaluating the features representing the health status to predict maintenance actions and remaning useful life of component. The evaluation is possible through pattern analysis of past and current measurements of the focused research components. Data mining visualization tools help in creating the most suitable patterns and learning insights from them. Estimations like features split values or measurement frequency of the component is achieved through classification methods in data mining. This paper presents how the quantitative results generated from data mining can be used to support decision making of domain experts.

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

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

  • 7.
    Holm, Magnus
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Cordero Garcia, Aimar
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Adamson, Göran
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Wang, Lihui
    KTH Royal Institute of Technology, Stockholm, Sweden.
    Adaptive decision support for shop-floor operators in automotive industry2014In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 17, p. 440-445Article in journal (Refereed)
    Abstract [en]

    Today's operators on factory shop-floors are often not stationed, dealing with a single or few tasks but have increasing responsibilities demanding enhanced skills and knowledge in a production environment where any disturbance must be settled with adequate actions without delay to keep optimum output. To be able to respond to these demands, the operators need dynamic, distributed and adaptive decision support in real-Time, helping them to distinguish decision options and maximizing productivity despite incoming stochastic events. The minimum of time and option for operators to consider appropriate action both during normal production and when facing unexpected or unscheduled events point out the need of adaptive decision support for operators. When initiating this research project the question from the industry partner was the following: In what ways is it possible to support operators in making decisions for optimal productivity? By targeting this problem this paper introduces a novel framework for an adaptive decision-support system enabled by event-driven function blocks and based on decision logics. The proposed decision support systems' ability to adapt to the actual conditions on the shop-floor is validated through a case study, and its capability is compared to the voice message system installed on-site.

  • 8.
    Linnéusson, Gary
    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. Jönköping University, Sweden.
    Aslam, Tehseen
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Relating strategic time horizons and proactiveness in equipment maintenance: a simulation-based optimization study2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 1293-1298Article in journal (Refereed)
    Abstract [en]

    Identifying sustainable strategies to develop maintenance performance within the short-termism framework is indeed challenging. It requires reinforcing long-term capabilities while managing short-term requirements. This study explores differently applied time horizons when optimizing the tradeoff between conflicting objectives, in maintenance performance, which are: maximize availability, minimize maintenance costs, and minimize maintenance consequence costs. The study has applied multi-objective optimization on a maintenance performance system dynamics model that contains feedback structures that explains reactive and proactive maintenance behavior on a general level. The quantified results provide insights on how different time frames are conditional to enable more or less proactive maintenance behavior in servicing production.

  • 9.
    Mattsson, Sandra
    et al.
    Chalmers University of Technology, Gothenburg, Sweden.
    Fast-Berglund, Åsa
    Chalmers University of Technology, Gothenburg, Sweden.
    Thorvald, Peter
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    A Relationship Between Operator Performance and Arousal in Assembly2016In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 44, p. 32-37Article in journal (Refereed)
    Abstract [en]

    In order to meet the challenges of future complex systems, manufacturing companies need to better understand how social sustainability affects the operator. One way of studying this is to investigate the possible relationships between operator performance and emotion in an assembly experiment. 60 participants took part in an experiment to investigate the relationships between operator performance and objective and subjective arousal. Results showed a weak relationship between operator performance and objective arousal but no significant relationship was found between performance and subjective arousal. The relationships indicate that further studies on operator emotion could be important to better assembly performance. A tool for doing this might be the Qsensor used in this experiment (measure of objective arousal). More studies are needed to further investigate found relationship and if objective emotion measures can be used to predict performance at assembly workstations.

  • 10.
    Mohammed, Abdullah
    et al.
    Department of Production Engineering, KTH Royal Institute of Technology, 100 44 Stockholm, Sweden.
    Schmidt, Bernard
    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 100 44 Stockholm, Sweden.
    Gao, Liang
    Huazhong University of Science and Technology, Hubei, China.
    Minimizing Energy Consumption for Robot Arm Movement2014In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 25, p. 400-405Article in journal (Refereed)
    Abstract [en]

    Robots are widely used in industry due to their efficiency and high performance. Many of them are operating in the manufacturing stage of the production line where the highest percentage of energy is consumed. Therefore, their energy consumption became a major focus for many robots manufacturers and academic research groups. Nevertheless, the optimisation of that consumption is still a challenging task which requires a deep understanding of the robot’s kinematic and dynamic behaviours. This paper proposes an approach to develop an optimisation module using Matlab® to minimise the energy consumptions of the robot’s movement. With the help of Denavit-Hartenberg notation, the approach starts first by solving the inverse kinematics of the robot to find a set of feasible joint configurations required to perform the task, solving the inverse kinematics is usually a challenging step which requires in-depth analyses of the robot. The module then solves the inverse dynamics of the robot to analyse the forces and torques applied on each joint and link in the robot. Furthermore, a calculation for the energy consumption is performed for each configuration. The final step of the process represents the optimisation of the calculated configurations by choosing the one with the lowest power consumption and sends the results to the robot controller. Three case studies are used to evaluate the performance of the module. The experimental results demonstrate the developed module as a successful tool for energy efficient robot path planning. Further analyses for the results have been done by comparing them with the ones from commercial simulation software. The case studies show that the optimisation of the location for the target path could reduce the energy consumption effectively.

  • 11.
    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).

  • 12.
    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.

  • 13.
    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.

  • 14.
    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.

  • 15.
    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.

  • 16.
    Schmidt, Bernard
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Gandhi, Kanika
    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. KTH Royal Institute of Technology, Stockholm, Sweden.
    Diagnosis of machine tools: assessment based on double ball-bar measurements from a population of similar machines2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 1327-1332Article in journal (Refereed)
    Abstract [en]

    The presented work is toward population-based predictive maintenance of manufacturing equipment with consideration of the automaticselection of signals and processing methods. This paper describes an analysis performed on double ball-bar measurement from a population ofsimilar machine tools. The analysis is performed after aggregation of information from Computerised Maintenance Management System,Supervisory Control and Data Acquisition, NC-code and Condition Monitoring from a time span of 4 years. Economic evaluation is performedwith use of Monte Carlo simulation based on data from real manufacturing setup.

  • 17.
    Senington, Richard
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Baumeister, Fabian
    University of Skövde, School of Engineering Science.
    Ng, Amos
    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.
    A linked data approach for the connection of manufacturing processes with production simulation models2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 70, p. 440-445Article in journal (Refereed)
    Abstract [en]

    This paper discusses the expected benefits of using linked data for the tasks of gathering, managing and understanding the data of smart factories. It has the further specific focus of using this data to maintaining a Digital Twin for the purposes of analysis and optimisation of such factories. The proposals are motivated by the use of an industrial example looking at the types of information required, the variation in data which is available and the requirements of an analysis platform to provide parameters for seamless, automated simulation and optimisation. 

  • 18.
    Senington, Richard
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Pataki, Balazs
    Hungarian Academy of Sciences Institute for Computer Science and Control, Budapest, Hungary.
    Wang, Xi Vincent
    KTH Royal Institute of Technology.
    Using docker for factory system software management: Experience report2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 659-664Article in journal (Refereed)
    Abstract [en]

    As factories become increasingly computerised, and with the increasing interest in Cyber-Physical-Systems and the Internet-of-Things, the issues of software management, deployment, configuration and integration are expected to become increasingly important. This paper reports on the ongoing experiences of using the Docker container technology in a major EU research project targeting smart factories. Docker is used to distribute, deploy and manage the configuration of multiple software modules between multiple teams and demonstrator sites in multiple locations, where each module can use its own mixture of protocols, programming languages and platforms.

  • 19.
    Zhang, Xiaoyang
    et al.
    Faculty of Engineering, Environment and Computing, Coventry University, Coventry, United Kingdom.
    Lu, Xin
    Faculty of Engineering, Environment and Computing, Coventry University, Coventry, United Kingdom.
    Wang, Sheng
    Faculty of Engineering, Environment and Computing, Coventry University, Coventry, United Kingdom.
    Wang, Wei
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Li, Weidong
    Faculty of Engineering, Environment and Computing, Coventry University, Coventry, United Kingdom.
    A multi-sensor based online tool condition monitoring system for milling process2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 1136-1141Article in journal (Refereed)
    Abstract [en]

    Tool condition monitoring has been considered as one of the key enabling technologies for manufacturing optimization. Due to the high cost and limited system openness, the relevant developed systems have not been widely adopted by industries, especially Small and Medium-sized Enterprises. In this research, a cost-effective, wireless communication enabled, multi-sensor based tool condition monitoring system has been developed. Various sensor data, such as vibration, cutting force and power data, as well as actual machining parameters, have been collected to support efficient tool condition monitoring and life estimation. The effectiveness of the developed system has been validated via machining cases. The system can be extended to wide manufacturing applications.

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