his.sePublications
Change search
Refine search result
1 - 38 of 38
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Adamson, Göran
    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.
    Moore, Philip
    Academy of Innovation & Research, Falmouth University, Cornwall, United kingdom.
    Wang, Lihui
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. KTH Royal Institute of Technology, Stockholm, Sweden.
    A Cloud Service Control Approach for Distributed and Adaptive Equipment Control in Cloud Environments2016In: Research and Innovation in Manufacturing: Key Enabling Technologies for the Factories of the Future - Proceedings of the 48th CIRP Conference on Manufacturing Systems / [ed] Roberto Teti, Elsevier, 2016, Vol. 41, p. 644-649Conference paper (Refereed)
    Abstract [en]

    A developing trend within the manufacturing shop-floor domain is the move of manufacturing activities into cloud environments, as scalable, on-demand and pay-per-usage cloud services. This will radically change traditional manufacturing, as borderless, distributed and collaborative manufacturing missions between volatile, best suited groups of partners will impose a multitude of advantages. The evolving Cloud Manufacturing (CM) paradigm will enable this new manufacturing concept, and on-going research has described many of its anticipated core virtues and enabling technologies. However, a major key enabling technology within CM which has not yet been fully addressed is the dynamic and distributed planning, control and execution of scattered and cooperating shop-floor equipment, completing joint manufacturing tasks.

    In this paper, the technological perspective for a cloud service-based control approach is described, and how it could be implemented. Existing manufacturing resources, such as soft, hard and capability resources, can be packaged as cloud services, and combined to create different levels of equipment or manufacturing control, ranging from low-level control of single machines or devices (e.g. Robot Control-as-a-Service), up to the execution of high level multi-process manufacturing tasks (e.g. Manufacturing-as-a-Service). A multi-layer control approach, featuring adaptive decision-making for both global and local environmental conditions, is proposed. This is realized through the use of a network of intelligent and distributable decision modules such as event-driven Function Blocks, enabling run-time manufacturing activities to be performed according to actual manufacturing conditions. The control system’s integration to the CM cloud service management functionality is also described.

  • 2.
    Adamson, Göran
    et al.
    University of Skövde, School of Technology and Society.
    Holm, Magnus
    University of Skövde, School of Technology and Society.
    Wang, Lihui
    University of Skövde, School of Technology and Society.
    Event-Driven Adaptability using IEC 61499 in Manufacturing Systems2012In: Proceedings of The 5th International Swedish Production Symposium, SPS12 / [ed] Mats Björkman, Linköping: The Swedish Production Academy , 2012, p. 453-460Conference paper (Refereed)
    Abstract [en]

    Different kinds of uncertainty, such as variations in manufacturing capability and functionality, as well as changes in demand, make up a dynamically changing environment for many manufacturing systems of today. The ability to adapt to these unforeseen changes, through dynamic decision-making as well as dynamic control capabilities based on the use of real-time manufacturing information and intelligence, is vital to be able to perform at a competitive level while reducing unscheduled downtime. The event-driven Function Block (FB) model of the IEC 61499 standard, as opposed to the time-triggered and data-driven concept of IEC 61331, supports this approach, making it possible to handle, in a responsive and adaptive way, different kinds of uncertainty. Our objective is to develop methodologies for distributed, adaptive and dynamic process planning as well as machine monitoring and control for machining and assembly operations, using event-driven FBs. The implementation and testing of FB-based control for manufacturing equipment has been successfully realized in prototype systems, with control of both CNC machining and robotic assembly operations. The approach of using IEC 61499 FBs for adaptive control in other applications is also investigated, as an adaptive decision support system for operators at manufacturing facilities is under development. We strongly believe that IEC 61499 will play a major role in the shift to adaptive manufacturing systems.

  • 3.
    Adamson, Göran
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Holm, Magnus
    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.
    Moore, Philip
    University College Falmouth, United Kingdom.
    Adaptive Assembly Feature Based Function Block Control of Robotic Assembly Operations2012In: The 13th Mechatronics Forum International Conference Proceedings: Vol. 1/3 / [ed] Rudolf Scheidl & Bernhard Jakoby, Linz: TRAUNER Verlag, 2012, p. 8-13Conference paper (Refereed)
    Abstract [en]

    Many manufacturing systems are exposed to a variety of unforeseen changes, negatively restricting their performances. External variations depending on market demand (e.g. changes in design, quantity and product mix) and internal variations in production capability and flexibility (e.g. equipment breakdowns, missing/worn/broken tools, delays and express orders) all contribute to an environment of uncertainty. In these dynamically changing environments, adaptability is a key feature for manufacturing systems to be able to perform at a maximum level, while keeping unscheduled downtime to a minimum. Targeting manufacturing equipment adaptability, this paper reports an assembly feature (AF) based approach for robotic assembly, using IEC 61499 compliant Function Blocks (FBs). Through the use of a network of event-driven FBs, an adaptive controller system for an industrial gantry robot’s assembly operations has been designed, implemented and tested. Basic assembly operations have been mapped as AFs into Assembly Feature Function Blocks (AF-FBs). Through their combination in FB networks, they can be aggregated to perform higher level assembly tasks. The AF-FBs dynamic execution and behavior can be adaptively controlled through embedded eventdriven algorithms, enabling the ability of adaptive decisions to handle unforeseen changes in the runtime environment.

  • 4.
    Adamson, Göran
    et al.
    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 100 44 Stockholm, Sweden.
    Holm, Magnus
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    The state of the art of cloud manufacturing and future trends2013In: Proceedings of the ASME 2013 International Manufacturing Science and Engineering Conference MSEC2013 June 10-14, 2013, Madison, Wisconsin, USA, ASME - The American Society of Mechanical Engineers , 2013, Vol. 2, p. Article number MSEC2013-1123-Conference paper (Refereed)
    Abstract [en]

    Cloud manufacturing has emerged as a new manufacturing paradigm, which combines technologies (such as Internet of Things, Cloud computing, semantic Web, virtualisation and service-oriented technologies) with advanced manufacturing models, information and communication technologies. It aims to be networked, intelligent, service-oriented, knowledge-based and energy efficient, and promises a variety of benefits and advantages by providing fast, reliable and secure on-demand services for users. It is envisioned that companies in all sectors of manufacturing will be able to package their resources and know-hows in the Cloud, making them conveniently available for others through pay-as-you-go, which is also timely and economically attractive. Resources, e.g. manufacturing software tools, applications, knowledge and fabrication capabilities, will then be made accessible to presumptive consumers on a worldwide basis. After surveying a vast array of available publications, this paper presents an up-to-date literature review together with future trends and research directions in Cloud manufacturing.

  • 5.
    Adamson, Göran
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Wang, Lihui
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Royal Institute of Technology, Stockholm, Sweden.
    Holm, Magnus
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Moore, Philip
    Falmouth University, Cornwall, UK.
    Adaptive Robot Control as a Service in Cloud Manufacturing2015In: ASME 2015 International Manufacturing Science and Engineering Conference: Volume 2: Materials; Biomanufacturing; Properties, Applications and Systems; Sustainable Manufacturing, ASME Press, 2015, Vol. 2, p. Paper No. MSEC2015-9479-Conference paper (Refereed)
    Abstract [en]

    The interest for implementing the concept of Manufacturing-as-a-Service is increasing as concepts for letting the manufacturing shop-floor domain take advantage of the cloud appears. Combining technologies such as Internet of Things, Cloud Computing, Semantic Web, virtualisation and service-oriented technologies with advanced manufacturing models, information and communication technologies, Cloud Manufacturing (CM) is emerging as a new manufacturing paradigm. The ideas of on-demand, scalable and pay-for-usage resource-sharing in this concept will move manufacturing towards distributed and collaborative missions in volatile partnerships. This will require a control approach for distributed planning and execution of cooperating manufacturing activities. Without control based on both global and local environmental conditions, the advantages of CM will not be fulfilled.

    By utilising smart and distributable decision modules such as event-driven FBs, run-time manufacturing operations in a distributed environment may be adjusted to prevailing manufacturing conditions. Packaged in a cloud service for manufacturing equipment control, it will satisfy the control needs in CM. By combining different resource types, such as hard, soft and capability resources, the cloud service Robot Control-as-a-Service can be realised.

    This paper describes the functional perspective and enabling technologies for a control approach for robotic assembly tasks in CM, and describes a scenario for its implementation.

  • 6.
    Adamson, Göran
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Wang, Lihui
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Kungliga Tekniska Högskolan, Stockholm (KTH).
    Holm, Magnus
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Moore, Philip
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Academy for Innovation & Research, Falmouth University, UK.
    Adaptive Robotic Control in Cloud Environments2014In: Proceedings of the 24th International Conference on Flexible Automation and Intelligent Manufacturing / [ed] F. Frank Chen, The University of Texas at San Antonio, U.S.A., Lancaster, Pennsylvania, USA: DEStech Publications, Inc , 2014, p. 37-44Conference paper (Refereed)
    Abstract [en]

    The increasing globalization is a trend which forces manufacturing industry of today to focus on more cost-effective manufacturing systems and collaboration within global supply chains and manufacturing networks. Cloud Manufacturing (CM) is evolving as a new manufacturing paradigm to match this trend, enabling the mutually advantageous sharing of resources, knowledge and information between distributed companies and manufacturing units. Providing a framework for collaboration within complex and critical tasks, such as manufacturing and design, it increases the companies’ ability to successfully compete on a global marketplace. One of the major, crucial objectives for CM is the coordinated planning, control and execution of discrete manufacturing operations in a collaborative and networked environment. This paper describes the overall concept of adaptive Function Block control of manufacturing equipment in Cloud environments, with the specific focus on robotic assembly operations, and presents Cloud Robotics as “Robot Control-as-a-Service” within CM.

  • 7.
    Adamson, Göran
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Wang, Lihui
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Department of Production Engineering, KTH Royal Institute of Technology, Stockholm, Sweden.
    Holm, Magnus
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Moore, Philip
    Academy for Innovation & Research, Falmouth University, Cornwall, United Kingdom.
    Cloud Manufacturing: A Critical Review of Recent Development and Future Trends2017In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 30, no 4-5, p. 347-380Article in journal (Refereed)
    Abstract [en]

    There is an on-going paradigm shift in manufacturing, in which modern manufacturing industry is changing towards global manufacturing networks and supply chains. This will lead to the flexible usage of different globally distributed, scalable and sustainable, service-oriented manufacturing systems and resources. Combining recently emerged technologies, such as Internet of Things, Cloud Computing, Semantic Web, service-oriented technologies, virtualisation and advanced high-performance computing technologies, with advanced manufacturing models and information technologies, Cloud Manufacturing is a new manufacturing paradigm built on resource sharing, supporting and driving this change.

    It is envisioned that companies in all sectors of manufacturing will be able to package their resources and know-hows in the Cloud, making them conveniently available for others through pay-as-you-go, which is also timely and economically attractive. Resources, e.g. manufacturing software tools, applications, knowledge and fabrication capabilities and equipment, will then be made accessible to presumptive consumers on a worldwide basis.

    Cloud Manufacturing has been in focus for a great deal of research interest and suggested applications during recent years, by both industrial and academic communities. After surveying a vast array of available publications, this paper presents an up-to-date literature review together with identified outstanding research issues, and future trends and directions within Cloud Manufacturing.

  • 8.
    Adamson, Göran
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Wang, Lihui
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Royal Institute of Technology, Stockholm, Sweden.
    Holm, Magnus
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Moore, Philip
    Falmouth University, Cornwall, United Kingdom.
    Feature-Based Adaptive Manufacturing Equipment Control for Cloud Environments2016In: Proceedings of the ASME 11th International Manufacturing Science and Engineering Conference, 2016, vol 2, American Society of Mechanical Engineers (ASME) , 2016, article id UNSP V002T04A019Conference paper (Refereed)
    Abstract [en]

    The ideas of on-demand, scalable and pay-for-usage resource-sharing in Cloud Manufacturing are steadily attracting more interest. For implementing the concept of Manufacturing as-a-Service in a cloud environment, description models and implementation language for resources and their capabilities are required. A standardized approach for systemived virtualization, servisilisation, retrieval, selection and composition into higher levels of functionality is necessary. For the collaborative sharing and use of networked manufacturing resources there is also a need for a control approach for distributed manufacturing equipment. In this paper, the technological perspective for an adaptive cloud service-based control approach is described, and a supporting information model for its implementation. The control is realized through the use of a network of intelligent and distributable Function Block decision modules, enabling run-time manufacturing activities to be performed according to actual manufacturing conditions. The control system's integration to the cloud service management functionality is described, as well as a feature-level capability model and the use of ontologies and the Semantic Web.

  • 9.
    Adamson, Göran
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Wang, Lihui
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Kungliga Tekniska Högskolan, Stockholm (KTH).
    Holm, Magnus
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Moore, Philip
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Academy for Innovation & Research, Falmouth University, UK.
    Function Block Approach for Adaptive Robotic Control in Virtual and Real Environments2014In: Proceedings of the 14th Mechatronics Forum International Conference / [ed] Leo J. De Vin and Jorge Solis, Karlstad: Karlstads universitet, 2014, p. 473-479Conference paper (Refereed)
    Abstract [en]

    Many manufacturing companies are facing an increasing amount of changes and uncertainty, caused by both internal and external factors. Frequently changing customer and market demands lead to variations in manufacturing quantities, product design and shorter product life-cycles, and variations in manufacturing capability and functionality contribute to a high level of uncertainty. The result is unpredictable manufacturing system performance, with an increased number of unforeseen events occurring in these systems. Such events are difficult for traditional planning and control systems to satisfactorily manage. For scenarios like these, with a dynamically changing manufacturing environment, adaptive decision making is crucial for successfully performing manufacturing operations. Relying on real-time information of manufacturing processes and operations, and their enabling resources, adaptive decision making can be realized with a control approach combining IEC 61499 event-driven Function Blocks (FBs) with manufacturing features. These FBs are small decision-making modules with embedded algorithms designed to generate the desired equipment control code. When dynamically triggered by event inputs, parameter values in their data inputs are forwarded to the appropriate algorithms, which generate new events and data output as control instructions. The data inputs also include monitored real-time information which allows the dynamic creation of equipment control code adapted to the actual run-time conditions on the shop-floor. Manufacturing features build on the concept that a manufacturing task can be broken down into a sequence of minor basic operations, in this research assembly features (AFs). These features define atomic assembly operations, and by combining and implementing these in the event-driven FB embedded algorithms, automatic code generation is possible. A test case with a virtual robot assembly cell is presented, demonstrating the functionality of the proposed control approach.

  • 10.
    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.

  • 11.
    De Vin, Leo J.
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Holm, Magnus
    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.
    The Information Fusion JDL-U model as a reference model for Virtual Manufacturing2010In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 26, no 6, p. 629-638Article in journal (Refereed)
    Abstract [en]

    This paper presents a description of Modelling and Simulation as used in the Virtual Systems Research Centre at the University of Skövde. It also gives a summarized account of issues discussed in previous work such as phases in a simulation project, Verification, Validation and Accreditation, and the use of simulation as a tool to reduce uncertainty. The role of the human in various phases/activities in simulation projects is highlighted. Examples of both traditional and advanced applications of Virtual Manufacturing are given. Examples of the latter are simulation-based monitoring and diagnostics, and simulation-based optimization. Two models for Information Fusion, the OODA loop and JDL-U model, are discussed, the latter being an extension of the JDL model that describes various levels of information fusion (JDL=“joint directors of laboratories”). Subsequently, the activities and phases in a Modelling and Simulation project are placed in the context of the JDL-U model. This comparison shows that there are very strong similarities between the six (0–5) levels in the JDL-U model and activities/phases in Modelling and Simulation projects. These similarities lead to the conclusion that the JDL-U model with its associated science base can serve as a novel reference model for Modelling and Simulation. In particular, the associated science base on the “user refinement” level could benefit the Virtual Manufacturing community.

  • 12.
    Frantzén, Marcus
    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.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Karlsson, V.
    Volvo Group Trucks Operations, Powertrain Production Skövde, Skövde, Sweden.
    Bremert, M.
    Volvo Group Trucks Operations, Powertrain Production Skövde, Skövde, Sweden.
    Dynamic maintenance priority of a real-world machining line2016In: Proceedings of the 7th Swedish Production Symposium, 2016Conference paper (Refereed)
    Abstract [en]

    To support the shop-floor operators, decision support systems (DSS) are becoming more and more vital to the success of manufacturing systems in industry today. In order to get a DSS able to adapt to disturbances in a production system, on-line data are needed to be able to make optimal or near-optimal decisions in real-time (soft real-time). This paper investigates one part of such a system, i.e. how different priorities of maintenance activities (planned and unplanned) affect the productivity of a production system. A discrete-event simulation model has been built for a real-world machining line in order to simulate the decisions made in subject to disturbances. This paper presents a way of prioritizing operators and machines based on multiple criteria such as competence, utilization, distance, bottleneck, and Work-In-Process. An experimental study based on the real-world production system has shown promising results and given insights of how to prioritize the operators in a good way. Another novelty introduced in this paper is the use of simulation-based optimization to generate composite dispatching rules in order to find good tradeoffs when taking a decision of which machine or operator to select.

  • 13.
    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

  • 14.
    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.

  • 15.
    Holm, Magnus
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Adaptive Decision Support for Shop-floor Operators using Function Blocks2017Doctoral thesis, monograph (Other academic)
    Abstract [en]

    In manual and semi-automation production systems, flexibility and adaptability are affected by the shop-floor operators’ skills, abilities and knowledge. Such dependencies highlight the vital importance of developing and utilising the knowledge, achievements and abilities of the operators working with production on the shop-floor. Teamwork, including both novice and highly experienced shop-floor operators, in a production environment with a high level of automation, is essential already today and is predicted to increase, when the complexity and demands of future production systems intensify. This trend is confirmed in both the research literature and by specialists within industry.

    The key to future competitiveness and effectiveness of the manufacturing industry is the shop-floor operators who handle the production systems. In addition, the future information intensive working environment, with its increasing complexity and less time available for decision-making, demands adaptive decision support and adaptive control systems that facilitate collaborative work on the shop-floor. It is therefore important to emphasise how decisions are supported in the time-limited working environment of the shop-floor, because this has a large impact on production output and quality and is vital to the success of the company. Consequently, this dissertation presents a framework for an adaptive decision support system that concentrates on shop-floor operators, in order to enhance their development and future contribution to leading edge production systems.

    The overall aim of the research presented is to define a framework for an Adaptive Decision Support System, to address the scope and demands of the future shop-floor, as indicated in the research literature, and confirm its relevance, as well as further elaborate it on the basis of interviews with production managers and HR specialists

    The research presented uses the design science research process. In parallel, decision support systems and the industrial shop-floor have been studied in the research literature and the current state of industrial practice has been assessed. These areas together form the basis for the research on adaptive decision support for shop-floor operators. A framework enabling adaptive decision support and adaptive system control, based on event-driven function block technology and Augmented Reality technology, is formulated.

    The gap of research on decision support for shop-floor operators, indicated in the research literature is addressed by the research preformed.  Adaptive and dynamic decision support and system control able to process vast amounts of information in real time demonstrates utility for shop-floor operators. The research presenting the Adaptive Decision Support System has demonstrated its utility for shop-floor systems and production operatives in two extensive studies using demonstrators based on real-life production environments.

    A methodology, the ‘User group’, has been formulated for research collaboration and bi-directional knowledge transfer between academia and the industrial partners. It provides tools that enable cooperation between the experienced research partner and the novices, despite their different levels of engagement in the same project, without dividing them into separate groups. The ‘user group’ case study presented describes how both the inexperienced and the research mature companies gain new knowledge and engage in ongoing research. By doing so, the industrial project partners have extensively supported the research presented and will subsequently be the expected beneficiaries.

  • 16.
    Holm, Magnus
    University of Skövde, School of Technology and Society.
    SIMBOSeer –Simulation Based Optimisation on low level Sequences of Operations.2008Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

     

    The aim of this project has been to develop a new method that can be used for optimising the sequences of operations in flexible manufacturing cells. The method combines existing methods and available software tools from three research areas, optimisation, flexibility and virtual manufacturing. This method is named SIMBOSeer and it combines genetic algorithms in discrete event simulation together with continuous robot simulation. SIMBOSeer has been implemented at an existing workcell at Volvo Powertrain, Skövde, and it has successfully shown to be able to find possible improvements of the sequences of operations. SIMBOSeer has shown to be a successful combination of different virtual manufacturing tools. It has a great ability to find an optimal solution of the sequence of operations in a flexible manufacturing cell. SIMBOSeer not only gives a fast answer on how to produce different variants it also offers the possibility to generate the robot code automatically.

  • 17.
    Holm, Magnus
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    The future shop-floor operators, demands, requirements and interpretations2018In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 47, p. 35-42Article in journal (Refereed)
    Abstract [en]

    The evolution of the manufacturing industry reveals continuous progress and development throughout the years. This evolution not only includes production methodologies and the production equipment, it also includes the working environment of the shop-floor operators. The demands faced by the shop-floor operators have developed from strictly controlled, simple and monotonic tasks to self-controlled team work requiring a holistic approach that aims at continuous improvements and achieving a high degree of flexibility, adaptability and initiative.

    This paper describes the evolution of the shop-floor operator, according to the research literature and interviews with manufacturing managers and human resources specialists. In addition, the paper presents the response of future Swedish shop-floor operators, today’s high-school students, to a description of their possible future work as shop-floor operators. The Swedish manufacturing industry competes, to a large extent, on and responds to the international market. The findings made in this paper are thus also interesting for other industries and countries acting on the international market.

  • 18.
    Holm, Magnus
    et al.
    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.
    Moore, Philip
    Academy of Innovation & Research, Falmouth University, Cornwall, United kingdom.
    Wang, Lihui
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. KTH Royal Institute of Technology, Stockholm, Sweden.
    Why I want to be a future Swedish shop-floor operator2016In: Research and Innovation in Manufacturing: Key Enabling Technologies for the Factories of the Future - Proceedings of the 48th CIRP Conference on Manufacturing Systems / [ed] Roberto Teti, Elsevier, 2016, Vol. 41, p. 1101-1106Conference paper (Refereed)
    Abstract [en]

    When looking in rear view mirrors the Swedish as well as the international production industries can overview several years of progress covering all aspects of production. Production methodologies and machines etc. have changed and evolved, and so has the environment of the shop-floor operator. The demands on the shop-floor operators have grown from simple monotonic tasks with low complexity to pro-active team work requiring flexibility, continuous improvements and a holistic approach. With a base in a study where production and HR-managers at six Swedish manufacturing industries have been interviewed this paper identifies the role of today’s and the future Swedish shop-floor operator. The response to the described role of the future operator is compiled from the ones who will become the future Swedish shop-floor operators – today’s teenagers attending technical high-school. Their views of the environment of the future shop-floor operator are described by accuracy, development, a good working environment and team work. The paper also reveals what the offer should include to make these teenagers say: I want to be a future Swedish shop-floor operator.

  • 19.
    Holm, Magnus
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Adamson, Göran
    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. Royal Institute of Technology, Stockholm, Sweden.
    Enhancing Adaptive Production Using IEC 61499 Event-Driven Function Blocks2013In: Proceedings of the North American Manufacturing Research Institution of SME, vol. 41, 10-14 June, University of Wisconsin-Madison, Society of Manufacturing Engineers, North American Manufacturing Research Institute of SME , 2013, p. 420-429Conference paper (Refereed)
    Abstract [en]

    Reduction of production costs and the ability to continuously improve is a must for every manufacturer. High availability in a dynamic and complex production environment demands adaptability to recurring changes. Each device within the production systems holds more and more intelligence and computing power which supports an approach implementing the standard of IEC 61499 to enhance adaptive production by enabling a distributed automation system with improved productivity. Research approaching IEC 61499 is investigated and reported in this paper, covering both control of manufacturing equipment and adaptive process planning. The objective is to develop methodologies for process planning as well as machine control and monitoring for machining and assembly operations in a dynamic, adaptive and distributed environment using event-driven function blocks.

  • 20.
    Holm, Magnus
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Adamson, Göran
    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.
    IEC 61499 - Enabling Control of Distributed Systems Beyond IEC 61131-32012In: Proceedings of the SPS12 conference 2012, Swedish Production Academy , 2012, p. 37-44Conference paper (Refereed)
  • 21.
    Holm, Magnus
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Adamson, Göran
    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.
    Moore, Philip
    University College Falmouth, United Kingdom.
    An IEC 61499 Function Block based Approach for CNC Machining Operations2012In: The 13th Mechatronics Forum International Conference Proceedings: Vol. 1/3 / [ed] Rudolf Scheidl & Bernhard Jakoby, Linz: TRAUNER Verlag, 2012, p. 115-121Conference paper (Refereed)
    Abstract [en]

    In order to create an adaptive and interoperable CNC control system to explore the full functionality of CNC machine tools and to surpass the shortcomings and restrictions of the current CNC control standard using G-codes, an IEC 61499 function block based control system model has been developed. Basic machining operations are identified and classified as machining features, which are wrapped into Machining Feature Function Blocks (MF-FBs) with algorithms. For the machining of a part, the required MF-FBs are selected and combined into a Composite Function Block, comprising the correct control instructions for machining the part.

    The event-driven nature of these function blocks enables the run-time selection of appropriate algorithms and control of their correct behavior and dynamic execution, supporting the system’s ability to act in response to actual conditions and manufacturing requirements. Being truly adaptive makes it possible that different available machine tools be selected to machine a part with the appropriate control code generated at runtime. This eliminates the tedious CNC programming effort, and therefore no predefined, machine-specific control code has to be generated in advance. The use of generic function blocks for encapsulation of machining know-how in algorithms makes machines and CNC systems independent and therefore portable, reusable and interoperable.

  • 22.
    Holm, Magnus
    et al.
    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.
    Moore, Philip
    Academy of Innovation & Research, Falmouth University, United Kingdom.
    Framework for an adaptive decision support system for industrial shop-floor operators2014Conference paper (Refereed)
    Abstract [en]

    Today’s shop-floor operators’ working tasks often stretches over a broad spectra of jobs; from ordinary production assignments to handling errors and performing maintenance. Demands for enhanced skills and knowledge are constantly raised to limit the consequences of tool breakage, machine down time and other stochastic events negatively affecting the production.

    To be able to meet these increasing demands a framework for a distributed and adaptive decision support system is proposed. It will help the shop-floor operator to distinguish between decision options and minimize time to consider appropriate actions to maximize productivity both during normal production and when facing unexpected or unscheduled events.

    In what ways is it possible to support operators in making decisions for optimal productivity?” was the opening question from the industry partner when beginning this research. Targeting this question a novel framework for an adaptive decision support system (DSS) enabled by event-driven function blocks, based on decision logics is proposed. Its ability to adapt to the actual conditions on the shop-floor is compared to a currently used voice message system in a test case.

  • 23.
    Holm, Magnus
    et al.
    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.
    Moore, Philip
    Academy of Innovation & Research, Falmouth University, United Kingdom.
    The Future Swedish Shop-Floor Operator – Interviews with Production Managers2014In: Proceedings of the sixth Swedish Production Symposium, 2014, 2014Conference paper (Refereed)
    Abstract [en]

    This paper is based on a study in which production and HR managers at six Swedish manufacturing industries have been interviewed about the role of the shop-floor operator, taking off in today’s situation in trying to identify the future one. As well as the production methods and the machines etc. in the production system continuously evolve, so does the environment of the shop-floor operator. Increasing complexity in the production systems raises demands on the operators’ ability to handle ICT-tools to gain decision support and knowledge needed in the future shop-floor environment. 

  • 24.
    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.

  • 25.
    Holm, Magnus
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Danielsson, Oscar
    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.
    Moore, Philip
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Wang, Lihui
    Sustainable Manufacturing, KTH Royal Institute of Technology, Kungliga Tekniska Högskolan, Stockholm.
    Adaptive instructions to novice shop-floor operators using Augmented Reality2017In: Journal of Industrial and Production Engineering, ISSN 2168-1015, Vol. 34, no 5, p. 362-374Article in journal (Refereed)
    Abstract [en]

    This paper presents a novel system using Augmented Reality and Expert Systems to enhance the quality and efficiency of shop-floor operators. The novel system proposed provides an adaptive tool that facilitates and enhances support on the shop-floor, due to its ability to dynamically customize the instructions displayed, dependent upon the competence of the user. A comparative study has been made between an existing method of quality control instructions at a machining line in an automotive engine plant and this novel system. It has been shown that the new approach outcompetes the existing system, not only in terms of perceived usability but also with respect to two other important shop-floor variables: quality and productivity. Along with previous research, the outcomes of these test cases indicate the value of using Augmented Reality technology to enhance shop-floor operators’ ability to learn and master new tasks.

  • 26.
    Holm, Magnus
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Doverborn, Josefine
    Ng, Amos
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    De Vin, Leo
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Optimisation of Operation Sequences in Flexible Manufacturing Cells using Virtual Manufacturing Tools2009In: Proceedings of the 19th International Conference on Flexible Automation and Intelligent Manufacturing / [ed] Farhad Nabhani, Teesside University , 2009, p. 1348-1355Conference paper (Refereed)
    Abstract [en]

    Manufacturing organisations are continuously forced to improve the way of working to maintain their competitiveness on the global market. To optimize a production facility requires not only an optimal design of the whole line but also its internal operations sequencing and scheduling during the operational phase. The use of Virtual Manufacturing tools such as Discrete Event Simulation and Computer Aided Robotics has been proven to be highly effective both for production system design and for operational analysis and improvement. This paper proposes a new optimisation method, named SIMBOSeer, which synergistically combines the areas of optimisation, flexibility and virtual manufacturing that integrates robot simulation with simulation-based optimisation. Evaluation of SIMBOSeer, as applied to an existing manufacturing cell at a powertrain manufacturing company in Sweden, has shown that it can be used as an iterative process of analysis and optimisation. The results, when using realistic what-if scenarios, clearly point out that SIMBOSeer can facilitate the optimisation of operation sequences and decrease the total cycle time of the manufacturing cell. This is due to the fact that many non-value adding functions, such as unnecessary tool changes, which have a great negative impact on the effectiveness of the flexible manufacturing cell, can be avoided. Whilst the use of SIMBOSeer has obvious advantages under normal operating conditions of the cell, its use become even more beneficial when disturbance like tool failures occur or when product variants are introduced to the cell.

  • 27.
    Holm, Magnus
    et al.
    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.
    Aslam, Tehseen
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Moore, Philip
    Falmouth University, Penryn, Cornwall, United Kingdom.
    Wang, Lihui
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. KTH Royal Institute of Technology, Stockholm, Sweden.
    A methodology facilitating knowledge transfer to both research experienced companies and to novice SMEs2017In: International Journal of Enterprise Network Management, ISSN 1748-1252, Vol. 8, no 2, p. 123-140, article id IJENM0080202Article in journal (Refereed)
    Abstract [en]

    In this paper, knowledge transfer is defined as a process of disseminating both technological and theoretical understanding as well as enhancing both industrial and academic knowledge through conducted research to project partners collaborating within a research project. To achieve this, a new methodology called 'user groups' is introduced. It facilitates knowledge transfer between project participants in collaborative research programs engaging both experienced and unexperienced partners regardless of level of input. The introduced methodology 'user groups' provides tools for collaborating with several research partners even though their levels of engagement in the project and prior research experience may vary without dividing them into separate groups. It enables all project partners to gain new knowledge and by so doing extending the knowledge society. The case study shows that the eight engaged companies are able to cooperate, achieve their own objectives and, both jointly and individually, contribute to the overall project goals.

  • 28.
    Holm, Magnus
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Givehchi, Mohammad
    University of Skövde.
    Mohammed, Abdullah
    University of Skövde.
    Wang, Lihui
    KTH Royal Institute of Technology, Stockholm, Sweden.
    Web based monitoring and control of distant Robotic Operations2012In: Proceedings of the ASME 2012 International Manufacturing Science and Engineering Conference MSEC2012 June 4-8, 2012, Notre Dame, Indiana, USA, ASME Press, 2012, p. 605-612Conference paper (Refereed)
    Abstract [en]

    In order to improve the production efficiency while facing today’s manufacturing uncertainty, responsive and adaptive capabilities for rapid production changes are essential. This paper presents how dynamic control and real-time monitoring (embedded in a web-based Wise-ShopFloor framework) can integrate virtual models with real shop floors. Wise-ShopFloor (Web-based integrated sensor-driven e-ShopFloor)uses Java technologies (e.g., Java Servlet and Java3D) for implementing the system. It allows the operators, both remote and on-site, to monitor and control machines, devices and operations on a shop floor, based on run-time information from the connected machines, devices and their sensors. Two case studies are presented to demonstrate the approach towards web-based adaptive manufacturing. The first demonstrating how OPC-technology is used to improve the monitoring and control capabilities of the production and the second one focusing  on remote control of a robot eliminating the need of motion planning and tedious robot programming.

  • 29.
    Syberfeldt, Anna
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ayani, Mikel
    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.
    A holistic solution for integrating a simulated twin of an automation system during the system’s entire life-cycle2018In: 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, p. 405-410Conference paper (Refereed)
    Abstract [en]

    This paper describes a project that attempts to develop a holistic solution for integrating a simulated twin of an automation system during the system’s entire life-cycle. With such holistic solution, virtual commission could be undertaken in all steps of the life-cycle which facilitates companies in realizing flexible and intelligent automation systems. Based on the simulated twin, the companies could easily and cost-efficiently evaluate modifications, make improvements, and train operators when changes in the production setup occurs due mass-customization or new products being introduced. This aids the companies in staying competitive on a global and rapidly changing market and meet the challenges coming with the forth industrial revolution, such as mass-customization and short product life-cycles.

  • 30.
    Syberfeldt, Anna
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ayani, Mikel
    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
    Royal Institute of Technology.
    Lindgren-Brewster, Rodney
    Volvo Cars Engine, Skövde, Sweden.
    Localizing Operators in the Smart Factory: A Review of Existing Techniques and systems2016In: Proceedings of 2016 International Symposium on Flexible Automation, IEEE Computer Society, 2016, p. 186-192Conference paper (Refereed)
    Abstract [en]

    The aim of this paper to give a comprehensive overview of existing techniques and state-of-the-art systems for indoor localization that could be adopted in smart factories of the future. We present different techniques for calculating the position of a moving object using signal transmission and signal measurement,and compare their advantages and disadvantages. The paper also includes a discussion of various localization systems available in the market and compares their most important features. It ends with a discussion of important issues to consider in future work in order to fully implement indoor, real-time localization of operators in the smart factory.

  • 31.
    Syberfeldt, Anna
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Danielsson, Oscar
    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.
    Ekblom, Tom
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Augmented Reality at the Industrial Shop-Floor2014In: Augmented and Virtual Reality / [ed] Lucio Tommaso De Paolis, Antonio Mongelli, Springer Berlin/Heidelberg, 2014, p. 201-209Conference paper (Refereed)
    Abstract [en]

    This paper describes a study of the potential of using augmented real-ityat the industrial shop-floor with the aim ofimprovingthe capability of the shop-floor operators. In the study, aprototype systemfor augmented reality is developed based on the Oculus Rift platform. The systemisevaluated through an experimentin which a physical three-dimensionalpuzzleis to be assembled.

  • 32.
    Syberfeldt, Anna
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Danielsson, Oscar
    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
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Royal Institute of Technology, Stockholm, Sweden.
    Dynamic operator instructions based on augmented reality and rule-based expert systems2016In: Research and Innovation in Manufacturing: Key Enabling Technologies for the Factories of the Future - Proceedings of the 48th CIRP Conference on Manufacturing Systems / [ed] Roberto Teti, Elsevier, 2016, Vol. 41, p. 346-351Conference paper (Refereed)
    Abstract [en]

    Augmented reality is currently a hot research topic within manufacturing and a great potential of the technique is seen. In this study, we aim to increase the knowledge of the adaptation and usability of augmented reality for the training of operators. We propose an approach of using dynamic information content that is automatically adjusted to the individual operator and his/her learning progress for increased efficiency and shorter learning times. The approach make use of the concept of expert systems from the field of artificial intelligence for determine the information content on-line. We develop a framework called "Augmented Reality Expert System" (ARES) that combines AR and expert systems. A proof-of-concept evaluation of the framework is presented in the paper and possible future extensions are discussed.

  • 33.
    Syberfeldt, Anna
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Danielsson, Oscar
    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
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Royal Institute of Technology, Stockholm, Sweden.
    Visual Assembling Guidance Using Augmented Reality2015In: Procedia Manufacturing, ISSN 2351-9789, Vol. 1, p. 98-109Article in journal (Refereed)
    Abstract [en]

    This paper describes a study of using the concept of augmented reality for supporting assembly line workers in carrying out their task optimally. By overlaying virtual information on real world objects – and thereby enhance the human’s perception of reality – augmented reality makes it possible to improve the visual guidance to the workers.  In the study, a prototype system is developed based on the Oculus Rift platform and evaluated using a simulated assembling task. The main aim is to investigate user acceptance and how this can possible be improved. 

  • 34.
    Syberfeldt, Anna
    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.
    Danielsson, Oscar
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Wang, Lihui
    Royal Institute of Technology, Stockholm, Sweden.
    Lindgren Brewster, Rodney
    Volvo Cars Engine, Skövde, Sweden.
    Support Systems on the Industrial Shop-floors of the Future: Operators' Perspective on Augmented Reality2016In: 6th CIRP Conference on Assembly Technologies and Systems (CATS) / [ed] Rikard Söderberg, Elsevier, 2016, Vol. 44, p. 108-113Conference paper (Refereed)
    Abstract [en]

    With augmented reality, virtual information can be overlaid on the real world in order to enhance a human’s perception of reality. In this study, we aim to deepen the knowledge of augmented reality in the shop-floor context and analyze its role within smart factories of the future. The study evaluates a number of approaches for realizing augmented reality and discusses advantages and disadvantages of different solutions from a shop-floor operator’s perspective. The evaluation is done in collaboration with industrial companies, including Volvo Cars and Volvo GTO amongst others. The study also identifies important future research directions for utilizing the full potential of the technology and successfully implement it on industrial shop-floors.

  • 35.
    Wang, Lihui
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Adamson, Göran
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Holm, Magnus
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Moore, Philip
    Mechatronics Research Centre, De Montfort University, Leicester LE1 9BH, United Kingdom.
    A review of function blocks for process planning and control of manufacturing equipment2012In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 31, no 3, p. 269-279Article, review/survey (Refereed)
    Abstract [en]

    Manufacturing in a job-shop environment is often characterized by a large variety of products in small batch sizes, requiring real-time monitoring for dynamic distributed decision making, and adaptive control capabilities that are able to handle, in a responsive way, different kinds of uncertainty, such as changes in demand and variations in production capability and functionality. In many manufacturing systems, traditional methods, based on offline processing performed in advance, are used. These methods are not up to the standard of handling uncertainty, in the dynamically changing environment of these manufacturing systems. Using real-time manufacturing intelligence and information to perform at a maximum level, with a minimum of unscheduled downtime, would be a more effective approach to handling the negative performance impacts of uncertainty. The objective of our research is to develop methodologies for distributed, adaptive and dynamic process planning as well as machine monitoring and control for machining and assembly operations, using event-driven function blocks. The implementation of this technology is expected to increase productivity, as well as flexibility and responsiveness in a job-shop environment. This paper, in particular, presents the current status in this field and a comprehensive overview of our research work on function block-enabled process planning and execution control of manufacturing equipment.

  • 36.
    Wang, Lihui
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Adamson, Göran
    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.
    Moore, Philip
    De Montfort University.
    Current Status of Function Blocks for Process Planning and Execution Control of Manufacturing Equipment2011In: Proceedings of the 21st International Conference on Flexible Automation and Intelligent Manufacturing, Feng Chia University , 2011, p. 963-973Conference paper (Refereed)
    Abstract [en]

    Manufacturing in a job-shop environment is often characterized by a large variety of products in small batch size, requiring real-time monitoring for dynamic distributed decision making, as well as dynamic control capabilities that are able to handle, in a responsive and adaptive way, different kinds of uncertainty, such as changes in demand and variations in production capability and functionality. In many manufacturing systems, traditional methods, based on offline processing performed in advance, are used. These methods are not up to the standard of handling uncertainty, in the dynamically changing environment of these manufacturing systems. Using real-time manufacturing intelligence and information to perform at a maximum level, with a minimum of unscheduled downtime, would be a more effective approach to handling the negative performance impacts of uncertainty. The objective of our research is to develop methodologies for distributed, adaptive and dynamic process planning as well a machine monitoring and control for machining and assembly operations, using event-driven function blocks. The implementation of this technology is expected to increase productivity, as well as flexibility and responsiveness in a job-shop environment. This paper, in particular, presents the current status in this field and a comprehensive overview of our research work on function block-enabled process planning and execution control of manufacturing equipment.

  • 37.
    Wang, Lihui
    et al.
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Givehchi, Mohammad
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Adamson, Göran
    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.
    A sensor-driven 3D model-based approach to remote real-time monitoring2011In: CIRP annals, ISSN 0007-8506, E-ISSN 1726-0604, Vol. 60, no 1, p. 493-496Article in journal (Refereed)
    Abstract [en]

    This paper presents an integrated approach for remote real-time monitoring of manufacturing operations. It is enabled by using virtual 3D models driven by real sensor data. The objectives of this research are twofold: (1) to significantly reduce network traffic for real-time monitoring over the Internet: and (2) to increase the controllability of manufacturing systems from anywhere in a decentralised environment. Particularly, this paper covers the principle of the approach, system architecture, prototype implementation, and a case study of remote control of a robotic assembly cell. Compared with camera-based monitoring systems, our approach only consumes less than 1% of its network bandwidth, feasible and practical as a web-based portable solution. (C) 2011 CIRP.

  • 38.
    Wang, Lihui
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Holm, Magnus
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Adamson, Göran
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Embedding a process plan in function blocks for adaptive machining2010In: CIRP annals, ISSN 0007-8506, E-ISSN 1726-0604, Vol. 59, no 1, p. 433-436Article in journal (Refereed)
    Abstract [en]

    This paper presents a function block enabled approach towards adaptive process planning and machining. A two-layer structure of supervisory planning and operation planning is proposed to separate generic data from machine-specific ones. The supervisory planning is only performed once, in advance, at the shop level to generate machine-neutral process plans, whereas the operation planning is carried out at runtime at the machine level to determine machine-specific operations. Such adaptive decision making is facilitated by event-driven algorithms embedded in the function blocks. It is expected that the new approach can greatly enhance the dynamism of fluctuating job-shop machining operations.

1 - 38 of 38
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf