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  • 201.
    Frantzén, Marcus
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Ng, Amos
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    A case study of applying simulation-based optimisation to a real-world scheduling problem2010In: ORbit, ISSN 1601-8893, no 17, p. 4-7Article in journal (Other (popular science, discussion, etc.))
  • 202.
    Frantzén, Marcus
    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.
    Production simulation education using rapid modeling and optimization: Successful studies2015In: 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: IEEE Press, 2015, p. 3526-3537Conference paper (Refereed)
    Abstract [en]

    A common issue facing many simulation educators is that students usually spend excessive time to struggle with the programming and statistic parts of the simulation courses, and simply very little time to learn running systems analysis. If the students are coming from industry, and not the campus, then the problem becomes even worse. We observed this problem around 2005 and started to develop a new simulation software, a factory conceptual design toolset, partly aimed to address this problem. A new set of educational courses has since then been developed around the software for teaching production systems analysis, with both the campus students and managers/engineers from industry in mind. In this paper, we briefly introduce the software and share our experiences and some representative, successful studies conducted by the students in the past years.

  • 203.
    Frantzén, Marcus
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Ng, Amos H. C.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Moore, Philip
    Computing Sciences and Engineering, De Montfort University Leicester, LE1 9BH, United Kingdom.
    A simulation-based scheduling system for real-time optimization and decision making support2011In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 27, no 4, p. 696-705Article in journal (Refereed)
    Abstract [en]

    This paper presents an industrial application of simulation-based optimization (SBO) in the scheduling and real-time rescheduling of a complex machining line in an automotive manufacturer in Sweden. Apart from generating schedules that are robust and adaptive, the scheduler must be able to carry out rescheduling in real time in order to cope with the system uncertainty effectively. A real-time scheduling system is therefore needed to support not only the work of the production planner but also the operators on the shop floor by re-generating feasible schedules when required. This paper describes such a real-time scheduling system, which is in essence a SBO system integrated with the shop floor database system. The scheduling system, called OPTIMISE scheduling system (OSS), uses real-time data from the production line and sends back expert suggestions directly to the operators through Personal Digital Assistants (PDAs). The user interface helps in generating new schedules and enables the users to easily monitor the production progress through visualization of production status and allows them to forecast and display target performance measures. Initial results from this industrial application have shown that such a novel scheduling system can help both in improving the line throughput efficiently and simultaneously supporting real-time decision making.

  • 204.
    Galar, Diego
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Luleå University of Technology, Luleå, Sweden.
    Kans, Mirka
    Linnaeus University, Kalmar, Sweden.
    Schmidt, Bernard
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Big Data in Asset Management: Knowledge Discovery in Asset Data by the Means of Data Mining2016In: Proceedings of the 10th World Congress on Engineering Asset Management (WCEAM 2015) / [ed] Kari T. Koskinen, Helena Kortelainen, Jussi Aaltonen,Teuvo Uusitalo, Kari Komonen, Joseph Mathew, Jouko Laitinen, Springer, 2016, p. 161-171Conference paper (Refereed)
    Abstract [en]

    Assets are complex mixes of complex systems, built from components which, over time, may fail. The ability to quickly and efficiently determine the cause of failures and propose optimum maintenance decisions, while minimizing the need for human intervention is necessary. Thus, for complex assets, much information needs to be captured and mined to assess the overall condition of the whole system. Therefore the integration of asset information is required to get an accurate health assessment of the whole system, and determine the probability of a shutdown or slowdown. Moreover, the data collected are not only huge but often dispersed across independent systems that are difficult to access, fuse and mine due to disparate nature and granularity. If the data from these independent systems are combined into a common correlated data source, this new set of information could add value to the individual data sources by the means of data mining. This paper proposes a knowledge discovery process based on CRISP-DM for failure diagnosis using big data sets. The process is exemplified by applying it on railway infrastructure assets. The proposed framework implies a progress beyond the state of the art in the development of Big Data technologies in the fields of Knowledge Discovery algorithms from heterogeneous data sources, scalable data structures, real-time communications and visualizations techniques.

  • 205.
    Gandhi, Kanika
    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.
    Machine maintenance decision support system: A systematic literature review2018In: Advances in Manufacturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11 – 13, 2018, Skövde, Sweden / [ed] Peter Thorvald, Keith Case, Amsterdam: IOS Press, 2018, p. 349-354Conference paper (Refereed)
    Abstract [en]

    Growing competition market situations have emerged the requirement of the real-time data, understanding data behaviour, and maintenance actions in the manufacturing system. The future decision-making process in manufacturing needs to be more flexible to adapt to various methods for maintenance decision support systems (MDSS). This paper classifies various application areas of MDSS through a systemic literature review. Specifically, it identifies the relationship between the machine maintenance areas and the processes in which it integrates different tools and techniques to develop MDSS. The accumulated information helps in analyzing trends and shortcomings to concentrate the efforts for future research work. The reviewed papers are selected based on the contents, application tool assessments and clustered by their application areas. Furthermore, it proposes a structure outlined based on the functional knowledge as well as the information flow design during the development of MDSS, along with the relationship among application areas.

  • 206.
    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.

  • 207.
    García-García, Daniel
    et al.
    Instituto de Tecnología de Materiales (ITM), Universitat Politècnica de València (UPV), Alicante, Spain.
    Balart, Rafael
    Instituto de Tecnología de Materiales (ITM), Universitat Politècnica de València (UPV), Alicante, Spain.
    Lopez-Martinez, Juan
    Instituto de Tecnología de Materiales (ITM), Universitat Politècnica de València (UPV), Alicante, Spain.
    Ek, Monica
    School of Engineering Sciences in Chemistry, Biotechnology and Health, Department of Fibre and Polymer Technology, KTH-Royal Institute of Technology, Stockholm, Sweden.
    Moriana, Rosana
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. School of Engineering Sciences in Chemistry, Biotechnology and Health, Department of Fibre and Polymer Technology, KTH-Royal Institute of Technology, Stockholm, Sweden.
    Optimizing the yield and physico-chemical properties of pine cone cellulose nanocrystals by different hydrolysis time2018In: Cellulose (London), ISSN 0969-0239, E-ISSN 1572-882X, Vol. 25, no 5, p. 2925-2938Article in journal (Refereed)
    Abstract [en]

    Cellulose nanocrystals (CNCs) were isolated for the first time from pine cones (PC) by alkali and bleaching treatments and subsequent sulfuric acid hydrolysis (64%) at 45 degrees C. The influence of the hydrolytic reaction time (30, 45, and 90 min) on the yield, chemical composition and structure, and thermal stability of CNCs was evaluated. The removal of non-cellulosic constituents during the alkaline and bleaching treatment resulted in high pure cellulosic fibres. The isolation of CNCs from these cellulosic fibres at different reaction times was verified by the nano-dimensions of the individual crystals (< 3 and < 335 nm of average diameter and length, respectively). The highest yield (15%) and the optimum CNCs properties in terms of aspect ratio, thermal stability and crystallinity were obtained for an extraction time of 45 min. PC appeared to be a new promising source of cellulose fibres and CNCs with potential to be applied as reinforcement in composites and for food-packaging.

  • 208.
    García-García, Daniel
    et al.
    Instituto de Tecnología de Materiales-ITM, Universitat Politècnica de València, Alicante, Spain.
    Lopez-Martínez, Juan
    Instituto de Tecnología de Materiales-ITM, Universitat Politècnica de València, Alicante, Spain.
    Rafael, Balart
    Instituto de Tecnología de Materiales-ITM, Universitat Politècnica de València, Alicante, Spain.
    Strömberg, Emma
    School of Engineering Science in Chemistry, Biotechnology and Health, Department of Fibre and Polymer Technology, KTH-Royal Institute of Technology, Stockholm, Sweden.
    Moriana, Rosana
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. School of Engineering Science in Chemistry, Biotechnology and Health, Department of Fibre and Polymer Technology, KTH-Royal Institute of Technology, Stockholm, Sweden.
    Reinforcing capability of cellulose nanocrystals obtained from pine cones in a biodegradable poly(3-hydroxybutyrate)/poly(ε-caprolactone) (PHB/PCL) thermoplastic blend2018In: European Polymer Journal, ISSN 0014-3057, E-ISSN 1873-1945, Vol. 104, p. 10-18Article in journal (Refereed)
    Abstract [en]

    In this work, different loads (3, 5 and 7 wt%) of pine cone cellulose nanocrystals (CNCs) were added to films ofpoly(3-hydroxybutyrate)/poly(ε-caprolactone) (PHB/PCL) blends with a composition of 75 wt% PHB and 25 wt% PCL (PHB75/PCL25). The films were obtained after solvent casting followed by melt compounding in anextruder and finally subjected to a thermocompression process. The influence of different CNCs loadings on themechanical, thermal, optical, wettability and disintegration in controlled compost properties of the PHB75/PCL25blend was discussed. Field emission scanning electron microscopy (FESEM) revealed the best dispersion of CNCson the polymeric matrix was at a load of 3 wt%. Over this loading, CNCs aggregates were formed enhancing thefilms fragilization due to stress concentration phenomena. However, the addition of CNCs improved the opticalproperties of the PHB75/PCL25films by increasing their transparency and accelerated the film disintegration incontrolled soil conditions. In general, the blend with 3 wt% CNCs offers the best balanced properties in terms ofmechanical, thermal, optical and wettability

  • 209.
    Gerdes, M.
    et al.
    Hamburg Univ Appl Sci, Aeroaircraft Design & Syst Grp, Hamburg, Germany..
    Galar, Diego
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Luleå Univ Technol, Div Operat & Maintenance Engn, Luleå, Sweden.
    Scholz, D.
    Hamburg Univ Appl Sci, Aeroaircraft Design & Syst Grp, Hamburg, Germany.
    Genetic algorithms and decision trees for condition monitoring and prognosis of A320 aircraft air conditioning2017In: International Journal of Condition Monitoring, ISSN 1354-2575, E-ISSN 1754-4904, Vol. 59, no 8, p. 424-433Article in journal (Refereed)
    Abstract [en]

    Unscheduled maintenance is a large cost driver for airlines, but condition monitoring and prognosis can reduce the number of unscheduled maintenance actions. This paper discusses how condition monitoring can be introduced into most systems by adopting a data-driven approach and using existing data sources. The goal is to forecast the remaining useful life (RUL) of a system based on various sensor inputs. Decision trees are used to learn the characteristics of a system. The data for the decision tree training and classification are processed by a generic parametric signal analysis. To obtain the best classification results for the decision tree, the parameters are optimised by a genetic algorithm. A forest of three different decision trees with different signal analysis parameters is used as a classifier. The proposed method is validated with data from an A320 aircraft from Etihad Airways. Validation shows that condition monitoring can classify the sample data into ten predetermined categories, representing the total useful life (TUL) in 10% steps. This is used to predict the RUL. There are 350 false classifications out of 850 samples. Noise reduction reduces the outliers to nearly zero, making it possible to correctly predict condition. It is also possible to use the classification output to detect a maintenance action in the validation data.

  • 210.
    Gerdes, Mike
    et al.
    Aero - Aircraft Design and Systems Group, Hamburg University of Applied Sciences, Hamburg, Germany.
    Galar, Diego
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Division of Operation and Maintenance Engineering, Luleå University of Technology, Luleå, Sweden.
    Fuzzy condition monitoring of recirculation fans and filters2016In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 7, no 4, p. 469-479Article in journal (Refereed)
    Abstract [en]

    A reliable condition monitoring is needed to be able to predict faults. Pattern recognition technologies are often used for finding patterns in complex systems. Condition monitoring can also benefit from pattern recognition. Many pattern recognition technologies however only output the classification of the data sample but do not output any information about classes that are also very similar to the input vector. This paper presents a concept for pattern recognition that outputs similarity values for decision trees. Experiments confirmed that the method works and showed good classification results. Different fuzzy functions were evaluated to show how the method can be adapted to different problems. The concept can be used on top of any normal decision tree algorithms and is independent of the learning algorithm. The goal is to have the probabilities of a sample belonging to each class. Performed experiments showed that the concept is reliable and it also works with decision tree forests (which is shown during this paper) to increase the classification accuracy. Overall the presented concept has the same classification accuracy than a normal decision tree but it offers the user more information about how certain the classification is.

  • 211.
    Gerdes, Mike
    et al.
    Hamburg University of Applied Sciences Aero - Aircraft Design and Systems Group, Hamburg, Germany / Luleå University of Technology, Division of Operation and Maintenance Engineering, Luleå, Sweden.
    Galar, Diego
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Luleå University of Technology, Division of Operation and Maintenance Engineering, Luleå, Sweden.
    Scholz, Dieter
    Hamburg University of Applied Sciences Aero - Aircraft Design and Systems Group, Hamburg, Germany.
    Decision Trees and the Effects of Feature Extraction Parameters for Robust Sensor Network Design2017In: Eksploatacja i Niezawodnosc - Maintenance and Reliability, ISSN 1507-2711, Vol. 19, no 1, p. 31-42Article in journal (Refereed)
    Abstract [en]

    Reliable sensors and information are required for reliable condition monitoring. Complex systems are commonly monitored by many sensors for health assessment and operation purposes. When one of the sensors fails, the current state of the system cannot be calculated in same reliable way or the information about the current state will not be complete. Condition monitoring can still be used with an incomplete state, but the results may not represent the true condition of the system. This is especially true if the failed sensor monitors an important system parameter. There are two possibilities to handle sensor failure. One is to make the monitoring more complex by enabling it to work better with incomplete data; the other is to introduce hard or software redundancy. Sensor reliability is a critical part of a system. Not all sensors can be made redundant because of space, cost or environmental constraints. Sensors delivering significant information about the system state need to be redundant, but an error of less important sensors is acceptable. This paper shows how to calculate the significance of the information that a sensor gives about a system by using signal processing and decision trees. It also shows how signal processing parameters influence the classification rate of a decision tree and, thus, the information. Decision trees are used to calculate and order the features based on the information gain of each feature. During the method validation, they are used for failure classification to show the influence of different features on the classification performance. The paper concludes by analysing the results of experiments showing how the method can classy different errors with a 75% probability and how different feature extraction options influence the information gain.

  • 212.
    Ghobakhloo, Morteza
    et al.
    Department of Industrial Engineering, Minab Higher Educational Center, University of Hormozgan, Bandar Abbas, Iran.
    Azar, Adel
    Department of Management and Economics, Tarbiat Modares University, Tehran, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Lean-green manufacturing: the enabling role of information technology resource2018In: Kybernetes, ISSN 0368-492X, E-ISSN 1758-7883, Vol. 47, no 9, p. 1752-1777Article in journal (Refereed)
    Abstract [en]

    Purpose – The purpose of this paper is to contribute to the existing knowledge about the relationships between information technology (IT), lean manufacturing (LM), organizational environmental issues and business performance.

    Design/methodology/approach – A questionnaire-based survey was conducted to collect data from 122 elite manufacturers, and the hypothesized relationships were tested using partial least squares structural equation modeling. Findings – IT competence in LM acts as a lower-order organizational capability, and its business value should be recognized through the intermediate roles of LM effectiveness and environmental management capability. Findings recommend that the net benefits of LM are mainly materialized through waste and pollution reduction and simplified implementation of proactive environmental practices.

    Research limitations/implications – Among other limitations, relying on a rather small sample size and cross-sectional data of this research, and lack of generalizability of findings, tends to have certain limitations. An interesting direction for future research would be to extend this research by assessing interaction of other types of IT resources with LM and organizational environmental issues.

    Practical implications – Both LM and proactive environmental management are information-intensive. Investment in both technological and human aspects of IT resource aimed at increasing the effectiveness of LM activities and proactive environmental practices is imperative for contemporary manufacturers.

    Originality/value – This study introduces the IT capability of IT competence in LM and two organizational capabilities of LM effectiveness and environmental management capability. By doing so, the study highlights the significant role of organizational environmental issues in devising firms’ IT and advanced manufacturing technology investment strategies in LM context.

  • 213.
    Ghobakhloo, Morteza
    et al.
    Department of Industrial Engineering, University of Hormozgan, Bandar Abbas, Iran / Department of Mechanical and Manufacturing Engineering, University Putra Malaysia, Serdang, Malaysia.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Corporate survival in Industry 4.0 era: the enabling role of lean-digitized manufacturing2019In: Journal of Manufacturing Technology Management, ISSN 1741-038X, E-ISSN 1758-7786Article in journal (Refereed)
    Abstract [en]

    purpose– The study demonstrates how small manufacturing firms can leverage their Information Technology (IT) resources to develop the lean-digitized manufacturing system that offers sustained competitiveness in the Industry 4.0 era.

    Design/methodology/approach – The study performs an in-depth 5-years case study of a manufacturing firm, and reports its journey from failure in the implementation of enterprise resource planning to its success in integrating IT-based technology trends of Industry 4.0 with the firm’s core capabilities and competencies while pursuing manufacturing digitization.

    Findings – Industry 4.0 transition requires the organizational integration of many IT-based modern technologies and the digitization of entire value chains. However, Industry 4.0 transition for smaller manufacturers can begin with digitization of certain areas of operations in support of organizational core strategies. Development of leandigitized manufacturing system is a viable business strategy for corporate survivability in the Industry 4.0 setting.

    Research limitations/implications – Although the implementation of lean-digitized manufacturing system is costly and challenging, this manufacturing strategy offers superior corporate competitiveness in the long run. Since this finding is rather limited to the present case study, assessing the business value of lean-digitized manufacturing system in a larger-scale research context would be an interesting avenue for future research.

    Practical implications – Industry 4.0 transition for typical manufacturers should commensurate with their organizational, operational, and technical particularities. Digitization of certain operations and processes, when aligned with the firm’s core strategies, capabilities, and procedures, can offer superior competitiveness even in Industry 4.0 era, meaning that the strategic plan for successful Industry 4.0 transition is idiosyncratic to each particular manufacturer.

    Social implications – Manufacturing digitization can have deep social implications as it alters inter and intra organizational relationships, causes unemployment among low-skilled workforce, and raises data security and privacy concerns. Manufacturers should take responsibility for their digitization process and steer it in a direction that simultaneously safeguards economic, social, and environmental sustainability.

    Originality/value – The strategic roadmap devised and employed by the case company for managing its digitization process can better reveal what manufacturing digitization, mandated by Industry 4.0, might require of typical manufacturers, and further enable them to better facilitate their digital transformation process.

  • 214.
    Ghobakhloo, Morteza
    et al.
    Department of Industrial Engineering, Minab Higher Educational Center, University of Hormozgan, Bandar Abbas, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Fontes, Dalila Benedita Machado Martins
    Faculty of Economics, Universidade do Porto, Porto, Portugal.
    Ching, Ng Tan
    Department of Mechanical and Material Engineering, Universiti Tunku Abdul Rahman - Kuala Lumpur Campus, Kuala Lumpur, Malaysia.
    Modeling lean manufacturing success2018In: Journal of Modelling in Management, ISSN 1746-5664, E-ISSN 1746-5672, Vol. 13, no 4, p. 908-931Article in journal (Refereed)
    Abstract [en]

    Purpose – The purpose of this study is to contribute to the existing knowledge about the process ofachieving Lean Manufacturing (LM) success.

    Design/methodology/approach – This study uses interpretive structural modeling and captures theopinions of a group of LM experts from a world-class Japanese automobile manufacturer, to map theinterrelationships among potential determinants of LM success. This study further uses the data from asurvey of 122 leading automobile part manufacturers by performing structural equation modeling toempirically test the research model proposed.

    Findings – Management support and commitment, financial resources availability, information technologycompetence for LM, human resources management, production process simplicity, supportive culture andsupply chain-wide integration are the key determinants that directly or indirectly determine the level ofachievement of LMsuccess.

    Research limitations/implications – The determinants of LM success as experienced by Asianautomobile manufacturers might be different from determinants of LM success as experienced byWestern automobile manufacturers. An interesting direction for future research would be to capturethe experts’ inputs from Western automobile manufacturers to complement the findings of thisstudy.

    Practical implications – The practical contribution of this study lays in the development of linkagesamong various LM success determinants. Utility of the proposed interpretive structural modeling andstructural equation modeling methodologies imposing order, direction and significance of therelationships among elements of LM success assumes considerable value to the decision-makers and LMpractitioners.

    Originality/value – Building on opinions of a group of LM experts and a case study of leading auto partmanufacturers, the present study strives to model the success of LM, a topic that has received little attentionto date.

  • 215.
    Givehchi, Mohammad
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Holm, Magnus
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Adamson, Göran
    University of Skövde, School of Engineering Science.
    Wang, Lihui
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Web-based Real-time Monitoring and Control of a Robot2011In: / [ed] Jan-Eric Ståhl, 2011Conference paper (Refereed)
    Abstract [en]

    In order to enhance production in today’s uncertain manufacturing environments, real-time monitoring and dynamic control capabilities that are responsive and adaptive to rapid changes of production capability and functionality are vital. Targeting the dynamic issue, this paper presents a virtual production aid, a Wise-ShopFloor(Web-based integrated sensor-driven e-ShopFloor) prototype that can integrate Web-based sensor-driven virtual models with a real shop floor.

    The Wise-ShopFloor utilizes Java technologies (e.g., Java 3D and Java Servlet) for system implementation which allows the users to monitor and control distant shop floor operations based on runtime information from the shop floor. Particularly, remote monitoring and control of an industrial robot is chosen as a case study to demonstrate the approach towards web-based adaptive manufacturing. It is envisioned that this approach not only can bridge the gap between virtual and real manufacturing but also can largely enhance manufacturing performance and profitability via remote instant assistance

  • 216.
    Givehchi, Mohammad
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Ng, Amos H. C.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Wang, Lihui
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Spot-welding sequence planning and optimization using a hybrid rule-based approach and genetic algorithm2011In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 27, no 4, p. 714-722Article in journal (Refereed)
    Abstract [en]

    Performing assembly planning to find a valid hierarchical assembling structure of a product (i.e. Manufacturing Bill of Materials or MBOM) based on the constraints and necessities inferred from or declared by different sources is potentially complicated. On the other hand, Engineering Changes (EC) may drastically affect the constraints and necessities which the planning of an MBOM was based on. Managing ECs to evaluate and propagate their effects on the upstream data used in assembly planning and downstream activities and information is crucial but problematic. Often it is possible to define a set of rules for the constraints and necessities of assembly planning and find solutions or check validity of solutions based on the rule-set. This paper proposes a rule-based assembly planning method and introduces the concepts and standard notations on how structured rule-sets can be derived from descriptive rules and then used in an algorithm for generating or validating MBOMs. The method was partially automated and successfully employed along with a commercial Virtual Manufacturing package integrated with an in-house developed GA-based sequence optimizer and applied to the sequence optimization in minimizing the cycle time of the robotic spot welding operations for a sheet-metal assembly found in automotive industry. (C) 2011 Elsevier Ltd. All rights reserved.

  • 217.
    Givehchi, Mohammad
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Wang, Lihui
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    An Evolutionary Operation Sequence Optimization Tool for Robotic Spot Welding Based on Collision-Free Path Planner in Virtual Manufacturing2011In: Proceedings of NAMRI/SME, Society of Manufacturing Engineers, North American Manufacturing Research Institution, NAMRI/SME , 2011, p. 88-98Conference paper (Refereed)
    Abstract [en]

    Many problems in the lifecycle of Product and Production Development (PPD) can be formulated as optimization problems. But in most of the real-world cases, they are too complex to be solved by analytical models or classical optimization methods. CAx and Virtual Manufacturing (VM) tools are on the other hand being employed to create virtual representation of products and processes before any physical realization is conducted. Synergy of these two domains is of interest in this paper where planning a process with the minimum cycle-time for assembling a spot welded sheet-metal product is desired. The methodology suggests an extendible virtual manufacturing-based optimization approach using evolutionary algorithms. Accordingly, a novel toolset with integration of evolutionary optimization and a commercial VM environment is developed. More specifically, the latest feature which takes advantage of the collision avoidant segment path planning functionality of the VM tool and integrates it with the sequence optimizer is described.

  • 218.
    Givehchi, Mohammad
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Ng, Amos
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Wang, Lihui
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    An Integrated Approach to Spot Welding Sequence Planning and Optimization2010In: Proceedings of the ASME 2010 International Manufacturing Science and Engineering Conference: Volume 2, New York: ASME Press, 2010, p. 543-551Conference paper (Refereed)
    Abstract [en]

    Almost   in   every   discipline   involved   in   Product   and Production Development (PPD), optimization problems arrive. These  real-world  problems  are  too  complex  to  be  solved  by analytical models and classical optimization methods. CAx and Virtual Manufacturing (VM) tools are on the other hand being employed   more  and   more  to   create   virtual  representation models  of  the  products  under  development  and  their  related production   facilities,   processes,   and   systems   in   a   virtual environment  before  any  physical  realization  is  conducted. Synergy of these two domains is of interest in this paper where a PPD problem requiring planning a process with the minimum cycle-time  for  assembling  a  spot  welded  sheet-metal  product was  solved.  The  methodology  suggests  an  extendible  virtual manufacturing-based optimization approach using evolutionary algorithms.  The  methodology  is  also  required  to  be  partially compliant   to   the   concept   of   integrated   Product-Process-Resource  planning  and  optimization.  An  optimization  tool  is developed  accordingly  for  operation  sequence  optimization integrated with a commercial VM environment.

  • 219.
    Givehchi, Mohammad
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Ng, Amos
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Wang, Lihui
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Evolutionary optimization of robotic assembly operation sequencing with collision-free paths2011In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 30, no 4, p. 196-203Article in journal (Refereed)
    Abstract [en]

    Many problems in the lifecycle of product and production development (PPD) can be formulated as optimization problems. But in most of the real-world cases, they are too complex to be solved by analytical models or classical optimization methods. CAx and virtual manufacturing (VM) tools are on the other hand being employed to create virtual representation of products and processes before any physical realization is conducted. Synergy of these two domains is of interest in this paper where planning a process with the minimum cycle-time for assembling a spot welded sheet-metal product is desired. The methodology suggests an extendible virtual manufacturing-based optimization approach using evolutionary algorithms. Accordingly, a novel toolset with integration of evolutionary optimization and a commercial VM environment is developed. More specifically, the latest feature which takes advantage of the collision avoidant segment path planning functionality of the VM tool and integrates it with the sequence optimizer is described. (C) 2011 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.

  • 220.
    Givehchi, Mohammad
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Schmidt, Bernard
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Wang, Lihui
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre. Department of Production Engineering Royal Institute of Technology, Stockholm, Sweden.
    Knowledge-based Operation Planning and Machine Control by Function Blocks in Web-DPP2013In: Advances in Sustainable and Competitive Manufacturing Systems: 23rd International Conference on Flexible Automation & Intelligent Manufacturing / [ed] Américo Azevedo, Springer, 2013, p. 665-679Conference paper (Refereed)
    Abstract [en]

    Today, the dynamic market requires manufacturing firms to possess high degree of adaptability and flexibility to deal with shop-floor uncertainties. Specifically, targeting SMEs active in the machining and metal cutting sector who normally deal with complex and intensive process planning problems, researchers have tried to address the subject. Among proposed solutions, Web-DPP elaborates a two-layer distributed adaptive process planning system based on function-block technology. Function-block enabled machine controllers are one of the elements of this system. In addition, intensive reasoning based on the features data of the products models, machining knowledge, and resource data is needed to be performed inside the function blocks in machine controller side. This paper reports the current state of design and implementation of a knowledge-based operation planning module using a rule-engine embedded in machining feature function blocks, and also the design and implementation of a common interface (for CNC milling machine controller and its specific implementation for a specific commercial controller) embedded in the machining feature function blocks for controlling the machine. The developed prototype is validated through a case-study.

  • 221.
    Givehchi Yazdi, Mohammad
    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.
    Wang, Lihui
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Operation Sequence Optimization using an extended Virtual Manufacturing tool2011In: Proceedings of the 4th Swedish Production Symposium, Lund, 2011, p. 383-390Conference paper (Refereed)
  • 222.
    Goienetxea, Ainhoa
    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. 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, The Virtual Systems Research Centre. Division of Industrial Engineering and Management, Department of Engineering Science, Uppsala University, Sweden.
    Bringing together Lean and simulation: a comprehensive review2019In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588XArticle, 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.

  • 223.
    Goienetxea Uriarte, Ainhoa
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Bringing Together Lean, Simulation and Optimization: Defining a framework to support decision-making in system design and improvement2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The rapid changes in the market including globalization, the requirement for personalizedproducts and services by the customers, shorter product life-cycles, the exponential growthof technological advances, and the demographical changes, will demand organizations toeffectively improve and design their systems in order to survive. This is the actual paradigmcharacterizing the industrial and service sectors. This scenario presents a considerablechallenge to decision makers who will need to decide about how to design and improve amore than ever complex system without compromising the quality of the decision taken.Lean, being a widely applied management philosophy with very powerful principles, itsmethods and tools are static in nature and have some limitations when it comes to the designand improvement of complex and dynamic systems. Some authors have proposed thecombined use of simulation with Lean in order to overcome these limitations. Furthermore,optimization and post-optimization tools coupled to simulation, provide knowledge aboutoptimal or nearly optimal system configurations to choose from. However, even if Leanprinciples, methods and tools, as well as simulation and optimization, pursue the objectiveof supporting organizations regarding system design and improvement, a bilateral approachfor their combination and its benefits have barely been addressed in the literature.Many studies focus only on how specific Lean tools and simulation can be combined, treatingLean purely as a toolbox and not considering how Lean can support the simulation process.The aim of this research is to address this knowledge gap by analyzing the mutualbenefits and presenting a framework for combining Lean, simulation and optimization tobetter support decision makers in system design and improvement where the limitationsof Lean tools and simulation are overcome by their combination. This framework includesa conceptual framework explaining the relationships between the Lean philosophy, methodsand tools with simulation and optimization; the purposes for this combination and stepby step processes to achieve these purposes; the identification of the roles involved in eachprocess; a maturity model providing guidelines on how to implement the framework; existingbarriers for the implementation; and ethical considerations to take into account. Anindustrial handbook has also been written which explains how to deploy the framework.The research has been conducted in three main stages including an analysis of the literatureand the real-world needs, the definition and formulation of the framework, and finally, itsevaluation in real-world projects and with subject matter experts. The main contributionof this research is the reflection provided on the bilateral benefits of the combination, aswell as the defined and evaluated framework, which will support decision makers take qualitydecisions in system design and improvement even in complex scenarios.

  • 224.
    Goienetxea Uriarte, Ainhoa
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Bringing together Lean, simulation and optimization in a framework for system design and improvement2018In: Proceedings of the Winter Simulation Conference, Gothenburg, 9-12 December, 2018 / [ed] M. Rabe, A. A. Juan, N. Mustafee, A. Skoogh, S. Jain, B. Johansson, Piscataway, New Jersey: IEEE, 2018, p. 4132-4133Conference paper (Refereed)
    Abstract [en]

    Is it beneficial to combine lean, simulation and optimization? And if so, how can they be combined for decision-making support in system design and improvement? This research proposes a framework that sets the basis for achieving beneficial interactions between the lean philosophy, methods and tools, and simulation-based optimization. A framework that gives the users the possibility to get better system understanding, conduct a deeper system analysis, and attain an optimal system design and improvement, and thereby, get better foundation for sustainable long time improvement. The framework has been tested in several realworld case studies. Moreover, surveys have been conducted to evaluate the perception of subject matter experts about its usefulness, as well as its usability and perceived quality by end users and decision makers, all of them reporting very positive results.

  • 225.
    Goienetxea Uriarte, Ainhoa
    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. Department of Industrial Engineering and Management, School of Engineering, Jönköping University, Sweden.
    Ruiz Zúñiga, Enrique
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Urenda Moris, Matías
    Department of Industrial Engineering and Management, School of Engineering, Jönköping University, Sweden.
    Improving the Material Flow of a Manufacturing Company via Lean, Simulation and Optimization2017In: Proceedings of the International Conference on Industrial Engineering and Engineering Management, IEEM2017, IEEE, 2017, p. 1245-1250Conference paper (Refereed)
    Abstract [en]

    Companies are continuously working towards system and process improvement to remain competitive in aglobal market. There are different methods that support companies in the achievement of that goal. This paper presents an innovative process that combines lean, simulation and optimization to improve the material flow of a manufacturing company. A description of each step of the process details the lean tools and principles taken into account, as well as the results achieved by the application of simulation and optimization.The project resulted in an improved layout and material flow that employs an automated guided vehicle. In addition, lean wastes related to transport, inventory levels as well as waiting times were reduced. The utilization of the process that combines lean, simulation and optimization was considered valuable for the success of the project.

  • 226.
    Goienetxea Uriarte, Ainhoa
    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. Department of Industrial Engineering and Management, School of Engineering, Jönköping University, Sweden.
    Urenda Moris, Matias
    Department of Industrial Engineering and Management, School of Engineering, Jönköping University, Sweden.
    Jägstam, Mats
    Department of Industrial Engineering and Management, School of Engineering, Jönköping University, Sweden.
    Lean, Simulation and Optimization: A maturity model2017In: Proceedings of the International Conference on Industrial Engineering and Engineering Management, IEEM2017, IEEE, 2017, p. 1310-1315Conference paper (Refereed)
    Abstract [en]

    This article presents a maturity model that can be applied to support organizations in identifying their current state and guiding their further development with regard to lean, simulation and optimization. The paper identifies and describes different maturity levels and offers guidelines that explain how organizations can grow from lower to higher levels of maturity. In addition, it attempts to provide the starting point for organizations that have applied lean or are willing to implement it and which may also be considering taking decisions in a more efficient way via simulation and optimization.

  • 227.
    Goienetxea Uriarte, Ainhoa
    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.
    Urenda Moris, Matías
    Division of Industrial Engineering and Management, Department of Engineering Science, Uppsala University, Uppsala, Sweden.
    Supporting the lean journey with simulation and optimization in the context of Industry 4.02018In: Procedia Manufacturing, E-ISSN 2351-9789, Vol. 25, p. 586-593Article in journal (Refereed)
    Abstract [en]

    The new industrial revolution brings important changes to organizations that will need to adapt their machines, systems and employees’ competences to sustain their business in a highly competitive market. Management philosophies such as lean will also need to adapt to the improvement possibilities that Industry 4.0 brings. This paper presents a review on the role of lean and simulation in the context of Industry 4.0. Additionally, the paper presents a conceptual framework where simulation and optimization will make the lean approach more efficient, speeding up system improvements and reconfiguration, by means of an enhanced decision-making process and supported organizational learning.

  • 228.
    Goienetxea Uriarte, Ainhoa
    et al.
    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.
    Urenda Moris, Matías
    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.
    How can decision makers be supported in the improvement of an emergency department?: A simulation, optimization and data mining approach2017In: Operations Research for Health Care, ISSN 2211-6923, E-ISSN 2211-6931, Vol. 15, p. 102-122Article in journal (Refereed)
    Abstract [en]

    The improvement of emergency department processes involves the need to take into considerationmultiple variables and objectives in a highly dynamic and unpredictable environment, which makes thedecision-making task extremely challenging. The use of different methodologies and tools to support thedecision-making process is therefore a key issue. This article presents a novel approach in healthcarein which Discrete Event Simulation, Simulation-Based Multi-Objective Optimization and Data Miningtechniques are used in combination. This methodology has been applied for a system improvementanalysis in a Swedish emergency department. As a result of the project, the decision makers were providedwith a range of nearly optimal solutions and design rules which reduce considerably the length of stayand waiting times for emergency department patients. These solutions include the optimal number ofresources and the required level of improvement in key processes. The article presents and discussesthe benefits achieved by applying this methodology, which has proven to be remarkably valuable fordecision-making support, with regard to complex healthcare system design and improvement.

  • 229.
    Goienetxea Uriarte, Ainhoa
    et al.
    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.
    Urenda Moris, Matías
    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.
    System design and improvement of an emergency department using Simulation-Based Multi-Objective Optimization2015In: Journal of Physics, Conference Series, ISSN 1742-6588, E-ISSN 1742-6596, Vol. 616, no 1, article id 012015Article in journal (Refereed)
    Abstract [en]

    Discrete Event Simulation (DES) is nowadays widely used to support decision makers in system analysis and improvement. However, the use of simulation for improving stochastic logistic processes is not common among healthcare providers. The process of improving healthcare systems involves the necessity to deal with trade-off optimal solutions that take into consideration a multiple number of variables and objectives. Complementing DES with Multi-Objective Optimization (SMO) creates a superior base for finding these solutions and in consequence, facilitates the decision-making process. This paper presents how SMO has been applied for system improvement analysis in a Swedish Emergency Department (ED). A significant number of input variables, constraints and objectives were considered when defining the optimization problem. As a result of the project, the decision makers were provided with a range of optimal solutions which reduces considerably the length of stay and waiting times for the ED patients. SMO has proved to be an appropriate technique to support healthcare system design and improvement processes. A key factor for the success of this project has been the involvement and engagement of the stakeholders during the whole process.

  • 230.
    Goienetxea Uriarte, Ainhoa
    et al.
    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.
    Urenda Moris, Matías
    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.
    Karlberg, Catarina
    Monitoring and Analysis Area, Health Department of Västra Götaland, Skövde, Sweden.
    Wallqvist, Pierre
    Monitoring and Analysis Area, Health Department of Västra Götaland, Skövde, Sweden.
    Improved system design of an emergency department through simulation-based multiobjective-optimization2014Conference paper (Refereed)
    Abstract [en]

    Healthcare facilities, and especially emergency departments (ED), are usually characterized by its complexity due to the variability and stochastic nature of the processes involved in the system. The combination of different flows of patients, staff and resources also increments the complexity of this kind of facilities. In order to increase its efficiency, many researchers have proposed discrete-event simulation (DES) as a powerful improvement tool. However, DES can be a limited approach in the case a simulation model has too many combinations of input parameters, complex correlations between the input and output parameters and different objective functions. Hence, to find the best configuration of a complex system, an approach combining DES and meta-heuristic optimization becomes an even more powerful improvement technique. Simulation-based multiobjective-optimization (SMO) is a promising approach to generate multiple trade-off solutions particularly when multiple conflicting objectives exist within a complex system. The generated solutions provide decision makers with feasible and optimal alternatives to improve, modify or design healthcare systems. The aim of this paper is to present the work done at the ED of the regional Hospital of Skövde in Sweden, where SMO implemented in modeFromtier has been successfully applied. The result and methodology present a successful approach for decision makers in healthcare systems to reduce the waiting time of patients saving considerable time, money and resources.

  • 231.
    Goienetxea Uriarte, Ainhoa
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Sellgren, Tommy
    Volvo Car Corporation.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Urenda Moris, Matías
    Uppsala University.
    Introducing simulation and optimization in the Lean continuous improvement standards in an automotive company2019In: Proceedings of the Winter Simulation Conference, Gothenburg, December 9-12, 2018 / [ed] M. Rabe, A. A. Juan, N. Mustafee, A. Skoogh, S. Jain, B. Johansson, Piscataway, New Jersey: IEEE, 2019, p. 3352-3363Conference paper (Refereed)
    Abstract [en]

    The highly competitive automobile market requires automotive companies to become efficient by continuously improving their production systems. This paper presents a case study where simulationbased optimization (SBO) was employed as a step within a Value Stream Mapping event. The aim of the study was to promote the use of SBO to strengthen the continuous improvement work of the company. The paper presents all the key steps performed in the study, including the challenges faced and a reflection on how to introduce SBO as a powerful tool within the lean continuous improvement standards.

  • 232.
    Goienetxea Uriarte, Ainhoa
    et al.
    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.
    Allert, Anna-Lena
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Tööj, Lars
    Industrial Development Center West Sweden AB.
    Karlsson, Mattias
    Industrial Development Center West Sweden AB.
    An Innovative Collaboration Between Industry, University and Nonprofit Agency, for a Competitive Industry: A Swedish case2011In: ICERI 2001: 4th International Conference of Education, Research and Innovation: Conference proceedings / [ed] I. Candel Torres, L. Gómez Chova, A. López Martínez, International Association of Technology, Education and Development, IATED , 2011, p. 4154-4162Conference paper (Refereed)
    Abstract [en]

    In a knowledge based economy, manufacturing industry has to continuously improve their operations, processes and develop their employees in order to remain competitive in the market.

    In this context, the collaboration between industry and universities becomes of vital importance. Universities and industry have traditionally maintained fairly informal or lose ways of cooperation when it comes to education. This article presents a fruitful cooperation which has been established between the University of Skövde, the Industrial Development Center in the region, IDC West Sweden AB, and the manufacturing industry.

    The paper describes the development, lessons learned and the outcome of more than 3 years’ experience of close collaboration between the different stakeholders. It presents a methodology, used by the consortium to help manufacturing industries to improve their competiveness using a well defined process including: a company analysis, applied education and long-term coaching. A special focus is put on a long-term commitment by all partners. This alliance has performed more than 140 company analysis, conducted applied education for more than 2500 employees from more than 120 companies and performed coaching of more than 80 companies on site. The trend is that these figures will increase over time.

    The established collaboration has been strengthened over this period of time by a number of shared research projects. One of these projects involves an evaluation of the impact that this presented consortium has had on the region´s industry. Lean Learning Academies is another project that has been funded by the European Union within the Lifelong Learning Program, with the aim to increase the competitiveness of European companies and enhance the employability of students.

  • 233.
    Goienetxea Uriarte, Ainhoa
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Urenda Moris, Matías
    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.
    Oscarsson, Jan
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Lean, Simulation and Optimization: A Win-Win combination2016In: 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, New Jersey: IEEE Computer Society, 2016, p. 2227-2238Conference paper (Refereed)
    Abstract [en]

    Lean and simulation analysis are driven by the same objective, how to better design and improve processes making the companies more competitive. The adoption of lean has been widely spread in companies from public to private sectors and simulation is nowadays becoming more and more popular. Several authors have pointed out the benefits of combining simulation and lean, however, they are still rarely used together in practice. Optimization as an additional technique to this combination is even a more powerful approach especially when designing and improving complex processes with multiple conflicting objectives. This paper presents the mutual benefits that are gained when combining lean, simulation and optimization and how they overcome each other´s limitations. A framework including the three concepts, some of the barriers for its implementation and a real-world industrial example are also described.

  • 234.
    Griggs, Terry
    et al.
    The Open University, UK.
    Stokes, Klara
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    On Pentagonal Geometries with Block Size 3, 4 or 52016In: Symmetries in Graphs, Maps, and Polytopes: 5th SIGMAP Workshop, West Malvern, UK, July 2014 / [ed] Jozef Širáň, Robert Jajcay, Springer, 2016, p. 147-157Chapter in book (Refereed)
  • 235.
    Gudfinnsson, Kristens
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Strand, Mattias
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Challenges with BI adoption in SMEs2017In: Proceedings of the 8th International Conference on Information, Intelligence, Systems & Applications (IISA), IEEE, 2017, , p. 6p. 172-177Conference paper (Refereed)
    Abstract [en]

    Business intelligence (BI) has become a well-known umbrella term both amongst academics and practitioners. Researchers have studied how companies can take advantage of BI and what challenges companies are facing when working with BI. However, research is mostly focused on large companies, despite the importance of small- and medium sized companies (SMEs) in both society and economically. This paper presents results of an in-depth qualitative case study on challenges faced by SMEs when adopting BI. The challenges are categorized according to a BI maturity model adopted as unit of assessment. The contribution of the results presented is two-folded; 1) It increases current literature regarding challenges when adopting BI in SMEs, and 2) It serves as guidance for SMEs on common pitfalls that ought to be avoided.

  • 236.
    Gudfinnsson, Kristens
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Strand, Mattias
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    On transforming into the data-driven decision-making era: current state of practice in manufacturing smes2018In: Advances in Manufacturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden / [ed] Peter Thorvald, Keith Case, Amsterdam: IOS Press, 2018, Vol. 8, p. 337-342Conference paper (Refereed)
    Abstract [en]

    Current research lacks details on how SMMEs are able to capitalize on how their IT-solutions supports data-driven decision-making. Such details are important for being able to support further development of SMMEs and assuring their sustainability and competitive edge. Prosperous SMMEs are vital due to their economical and societal importance. To alleviate the lack of details, this paper presents the results of four case studies towards SMMEs partly aimed at investigating their current state of data-driven decision-making. The findings reveal that IT-solutions in some areas are either underdeveloped or unexplored. Instead, the SMMEs tend to focus on traditional manufacturing techniques, continuous improvements in the manufacturing process, and manual support routines and thereby neglects opportunities offered in relation to e.g. incident management, product quality monitoring, and the usage of KPIs not directly linked to manufacturing.

  • 237.
    Gudfinnsson, Kristens
    et al.
    University of Skövde, The Informatics Research Centre. University of Skövde, School of Informatics.
    Strand, Mattias
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Berndtsson, Mikael
    University of Skövde, The Informatics Research Centre. University of Skövde, School of Informatics.
    Analyzing Business Intelligence Maturity2015In: Journal of Decision Systems, ISSN 1246-0125, E-ISSN 2116-7052, Vol. 24, no 1, p. 37-54Article in journal (Refereed)
    Abstract [en]

    Business intelligence has fundamentally changed how companiesconduct their business. In literature, the focus has been on volume-operationcompanies that provide services to millions of customers. In contrast, complexsystemscompanies have fewer customers and pursue customer needs byproviding more customized products and services. This paper presents the resultsof a case study conducted at a complex-systems company, with the overall aim toidentify how complex-systems companies may take advantage of businessintelligence. A framework was used to measure business intelligence maturity ofthe company. In addition, we also explain the current maturity level of the casecompany,based on critical factors for success adopted from the literature. Indoing so, we also contribute on important details regarding factors that must beconsidered by organizations, in order to leverage their analytical capability.Finally, we also propose topics that need to be further investigated, in order toincrease current knowledge regarding BI usage and maturity in complex-systemscompanies.

  • 238.
    Gustavsson, Patrik
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Using Speech Recognition, Haptic Control and Augmented Reality to enable Human-Robot Collaboration in Assembly Manufacturing: Research Proposal2016Report (Other academic)
    Abstract [en]

    In recent years robots have become more adaptive and aware of the surroundings which enables them for use in human-robot collaboration. By introducing robots into the same working cell as the human, then the two can collaborate by letting the robot deal with heavy lifting, repetitive and high accuracy tasks while the human focuses on tasks that needs the flexibility of the human. Collaborative robots already exists today in the market but the usage of these robots are mainly to work in close proximity.

    Usually a teaching pendant is used to program a robot by moving it using a joystick or buttons. Using this teaching pendant for programming is usually quite slow and requires training which means that few can operate it. However, recent research shows that there exist several application using multi-modal communication systems to improve the programming of a robot. This kind of programming will be necessary to collaborate with a robot in the industry since the human in a collaborative task might have to teach the robot how to execute its task.

    This project aims to introduce a programming-by-guidance system into assembly manufacturing where the human can assist the robot by teaching the robot how to execute its task. Three technologies will be combined, speech recognition, haptic control, and augmented reality. The hypothesis is that with these three technologies an effective and intuitive programming-by-guidance system can be used within the assembly manufacturing industry. This project have three main motivators: Allowing workers, with no robot programming expertise, to teach the robot how to execute its task in an assembly manufacturing system; Reducing the development time of the robot by introducing advanced programming-by-guidance technology; Showing that augmented reality can add additional information that is useful when programming the robot.

  • 239.
    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.

  • 240.
    Gustavsson, Patrik
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    A New Algorithm Using the Non-dominated Tree to improve Non-dominated Sorting2018In: Evolutionary Computation, ISSN 1063-6560, E-ISSN 1530-9304, Vol. 26, no 1, p. 89-116Article in journal (Refereed)
    Abstract [en]

    Non-dominated sorting is a technique often used in evolutionary algorithms to determine the quality of solutions in a population. The most common algorithm is the Fast Non-dominated Sort (FNS). This algorithm, however, has the drawback that its performance deteriorates when the population size grows. The same drawback applies also to other non-dominating sorting algorithms such as the Efficient Non-dominated Sort with Binary Strategy (ENS-BS). An algorithm suggested to overcome this drawback is the Divide-and-Conquer Non-dominated Sort (DCNS) which works well on a limited number of objectives but deteriorates when the number of objectives grows. This paper presents a new, more efficient, algorithm called the Efficient Non-dominated Sort with Non-Dominated Tree (ENS-NDT). ENS-NDT is an extension of the ENS-BS algorithm and uses a novel Non-Dominated Tree (NDTree) to speed up the non-dominated sorting. ENS-NDT is able to handle large population sizes and a large number of objectives more efficiently than existing algorithms for non-dominated sorting. In the paper, it is shown that with ENS-NDT the runtime of multi-objective optimization algorithms such as the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) can be substantially reduced.

  • 241.
    Gustavsson, Patrik
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Brewster, Rodney
    Volvo Car Corporation, Skövde, Sweden.
    Wang, Lihui
    KTH Royal Institute of Technology, Stockholm, Sweden.
    Human-Robot Collaboration Demonstrator Combining Speech Recognition and Haptic Control2017In: Manufacturing Systems 4.0 - Proceedings of the 50th CIRP Conference on Manufacturing Systems / [ed] Mitchell M. Tseng, Hung-Yin Tsai, Yue Wang, 2017, Vol. 63, p. 396-401Conference paper (Refereed)
    Abstract [en]

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

  • 242.
    Hanson, Lars
    et al.
    Lund University.
    Högberg, Dan
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Use of Anthropometric Measures and Digital Human Modelling Tools for Product and Workplace Design2012In: Handbook of Anthropometry: Physical Measures of Human Form in Health and Disease / [ed] Victor R. Preedy, Springer Science+Business Media B.V., 2012, p. 3015-3034Chapter in book (Refereed)
    Abstract [en]

    This chapter addresses and demonstrates the application of digital human modelling (DHM) tools to consider anthropometric diversity in product and workplace design. A number of additional methods for evaluating ergonomics conditions are also illustrated. Three cases show how DHM tools can be applied in different design settings and for different design undertakings, focusing on user variation in anthropometry. A number of methods for user representation in the DHM tool are briefl y presented. Method selection depends on the design problem at hand, and the chapter exemplifies the use of different methods for different design tasks. Examples are the use of onedimensional percentile based statistics data, the use of predefined collections of manikins, and the creation of representative cases by using multidimensional statistics. The chapter takes a designer’s view of the uses of DHM tools for anthropometry-related issues and illustrates how the tools can be of value in the design process.

  • 243.
    Hanson, Lars
    et al.
    Chalmers University of Technology.
    Högberg, Dan
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Bohlin, Robert
    Chalmers Science Park.
    Carlsson, Johan S.
    Chalmers Science Park.
    IMMA - Intelligently Moving Manikin - Project Status2010In: Proceedings of the 3rd Applied Human Factors and Ergonomics (AHFE) International Conference / [ed] Gavriel Salvendy, Waldemar Karwowski, Louisville: AHFE International , 2010Conference paper (Refereed)
    Abstract [en]

    The overall rationale and assumption for the research project presented in this paper is that a fast, easy to use, and reliable procedure to predict and validate manual assembly tasks is of major importance in product and production development processes to ensure high and robust product quality and process performance. A basic condition for the research is the belief that tools with such functionality are currently not available for companies to utilise in their development processes. Hence more research and development is needed in the area. This paper describes the basic concepts and initial steps taken in the recently commenced research project IMMA - Intelligently Moving Manikin.

  • 244.
    Hanson, Lars
    et al.
    Industrial Development, Scania CV.
    Högberg, Dan
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Bohlin, Robert
    Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park.
    Carlsson, Johan S.
    Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park.
    IMMA - Intelligently Moving Manikins: Project Status 20112011In: Proceedings of the 1st International Symposium on Digital Human Modeling, Lyon, France, June, Université Claude Bernard Lyon , 2011Conference paper (Refereed)
    Abstract [en]

    The overall rationale and assumption for the research project presented in this paper is that a fast, easy to use, and reliable procedure to predict and validate manual assembly tasks is of major importance in product and production development processes to ensure high and robust product quality and process performance. A basic condition for the research is the belief that tools with such functionality are currently not available for companies to utilise in their development process. Hence more research and development is needed in the area. This paper describes the status of the project IMMA - Intelligently Moving Manikins and discusses coming initiatives. The project status is portrayed by a conceivable simulation task of a digital test assembly of a centre console.

  • 245.
    Hanson, Lars
    et al.
    Scania CV / Chalmers.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Carlson, Johan S
    Fraunhofer Chalmers Centre.
    Bohlin, Robert
    Fraunhofer Chalmers Centre.
    Brolin, Erik
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Chalmers.
    Delfs, Niclas
    Fraunhofer Chalmers Centre.
    Mårdberg, Peter
    Fraunhofer Chalmers Centre.
    Stefan, Gustafsson
    Fraunhofer Chalmers Centre.
    Keyvani, Ali
    Högskolan Väst / Chalmers.
    Rhen, Ida-Märta
    Fraunhofer Chalmers Centre / Chalmers.
    IMMA – Intelligently moving manikins in automotive applications2014Conference paper (Other academic)
  • 246.
    Hanson, Lars
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Högberg, Dan
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Carlson, Johan S.
    Geometry and Motion Planning group, Fraunhofer-Chalmers Center, Göteborg, Sweden.
    Delfs, Niclas
    Geometry and Motion Planning group, Fraunhofer-Chalmers Center, Göteborg, Sweden.
    Brolin, Erik
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Mårdberg, Peter
    Geometry and Motion Planning group, Fraunhofer-Chalmers Center, Göteborg, Sweden.
    Spensieri, Domenico
    Geometry and Motion Planning group, Fraunhofer-Chalmers Center, Göteborg, Sweden.
    Björkenstam, Staffan
    Geometry and Motion Planning group, Fraunhofer-Chalmers Center, Göteborg, Sweden.
    Nyström, Johan
    Geometry and Motion Planning group, Fraunhofer-Chalmers Center, Göteborg, Sweden.
    Ore, Fredrik
    School of Innovation, Design and Engineering, Mälardalen University, Eskilstuna, Sweden.
    Industrial path solutions - intelligently moving manikins2019In: DHM and Posturography / [ed] Sofia Scataglini, Gunther Paul, London: Academic Press, 2019, p. 115-124Chapter in book (Other academic)
    Abstract [en]

    IPS IMMA (Industrial Path Solutions - Intelligently Moving Manikins) is a digital human modeling tool developed in close cooperation between academia and industry in Sweden. The academic consortium behind the software consists of expertise within applied mathematics, ergonomics, and engineering. The development of IMMA was initiated from the vehicle industries’ need of an effective, efficient, objective, and user-friendly software for verification of manufacturing ergonomics. The ‘Industrial path solutions - intelligently moving manikins’ chapter consists of two main sections: the first about the commercially available tool, and the second about current or recent research projects developing the software further. Commercial IPS IMMA is presented by describing the biomechanical model and appearance, anthropometrics module, motion prediction, instruction language, and ergonomics evaluation. The research projects focus on dynamic motions simulation, muscle modelling and application areas such as human-robot collaboration, occupant packaging, and layout planning.

  • 247.
    Hanson, Lars
    et al.
    Lund University.
    Högberg, Dan
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Lundström, Daniel
    University of Skövde.
    Wårell, Maria
    ArjoHuntleigh R&D Center, Lund.
    Application of Human Modelling in Health Care Industry2009In: Digital Human Modeling: Second International Conference, ICDHM 2009 Held as Part of HCI International 2009 San Diego, CA, USA, July 19-24, 2009 Proceedings / [ed] Vincent G. Duffy, Springer Berlin/Heidelberg, 2009, p. 521-530Conference paper (Refereed)
    Abstract [en]

    Digital human modelling (DHM) is commonly utilised for vehicle and workplace design in the automotive industry. More rarely are the tools applied in the health care industry, albeit having similar objectives for cost-efficiency and user-centred design processes. The paper illustrates how a DHM tool is modified and utilised to evaluate a bathing system design from caretakers' and caregivers' ergonomics point of view. Anthropometry, joint range of motion, description and appearance of the manikin was customised to meet the requirements in a health care setting. Furthermore, a preferred bathing posture was defined. A suggested DHM working process scenario illustrates that DHM tools can be customised, applied and useful in health care product design. Except technical customisations of the DHM tool, the development of a working process and work organisation around the tool is proposed for an effective and efficient use of digital human modelling.

  • 248.
    Hanson, Lars
    et al.
    Industrial Development, Scania CV AB, Södertälje, Sweden / Wingquist Laboratory, Chalmers University of Technology, Göteborg, Sweden.
    Högberg, Dan
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Söderholm, M.
    Industrial Development, Scania CV AB, Södertälje, Sweden.
    Digital test assembly of truck parts with the IMMA-tool - an illustrative case2012In: Work: A journal of Prevention, Assesment and rehabilitation, ISSN 1051-9815, E-ISSN 1875-9270, Vol. 41, no Suppl 1, p. 2248-2252Article in journal (Refereed)
    Abstract [en]

    Several digital human modelling (DHM) tools have been developed for simulation and visualisation of human postures and motions. In 2010 the DHM tool IMMA (Intelligently Moving Manikins) was introduced as a DHM tool that uses advanced path planning techniques to generate collision free and biomechanically acceptable motions for digital human models (as well as parts) in complex assembly situations. The aim of the paper is to illustrate how the IPS/IMMA tool is used at Scania CV AB in a digital test assembly process, and to compare the tool with other DHM tools on the market. The illustrated case of using the IMMA tool, here combined with the path planner tool IPS, indicates that the tool is promising. The major strengths of the tool are its user friendly interface, the motion generation algorithms, the batch simulation of manikins and the ergonomics assessment methods that consider time.

  • 249.
    Hanson, Robin
    et al.
    Institutionen för teknikens ekonomi och organisation, Logistik och transport, Chalmers.
    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 supply2011In: Proceedings from the 4th International Swedish Production Symposium, 2011, p. 312-321Conference paper (Refereed)
  • 250.
    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.

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