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  • 1.
    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

  • 2.
    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.

  • 3.
    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.

  • 4.
    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.

  • 5.
    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.

  • 6.
    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.

  • 7.
    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)
  • 8.
    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.

  • 9.
    Mohammed, Abdullah
    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.
    Wang, Lihui
    University of Skövde, School of Technology and Society. University of Skövde, The Virtual Systems Research Centre.
    Interfacing Image Processing with Robotic Sketching2012In: Proceedings of the FAIM 2012, 22nd International Conference on Flexible Automation and Intelligent Manufacturing, June 10th-13th, 2012, Helsinki, Finland / [ed] Hasse Nylund, Satu Kantti, Ville Toivonen & Seppo Torvinen, Tampere: Tampere University of Technology, 2012, p. 285-294Conference paper (Refereed)
    Abstract [en]

    In attempt to have a flexible manufacturing environment with adaptive control systems, several researchers tend to integrate vision systems into the industrial systems to achieve that objective; the majority of the research works that have been done in this perspective tend to keep this kind of integration fully automated. Along the same direction, this paper presents an approach for integrating Robotic Sketching and Path Planning with Image Processing, and it introduces at the same time the ability for operators to remotely control and monitor the processing stages. It has been accomplished using network based architecture consisting of a vision system together with a server, a client and an ABB industrial robot. The aims of this paper are: (1) to provide an example that illustrates the benefit of interfacing the image processing techniques with the industrial shop floor system, and (2) to develop a web based system that allows an operator to remotely monitor and control the stages of the application using Java based applet. Further analyses have been done for the processing times of the application; this helped us to address the problem that consumed the largest proportion of the processing time. The work that has been done in this research provides additional supervision ability for the integrated system, and it demonstrates some of the challenges and the obstacles that may face this kind of integration.

  • 10.
    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.
    Web-DPP: An adaptive approach to planning and monitoring of job-shop machining operations2011In: Proceedings of the 7th CIRP-Sponsored International Conference on Digital Enterprise Technology, Athens, Greece, 2011, University of Patras , 2011Conference paper (Refereed)
    Abstract [en]

    Utilising the existing IT infrastructure, the objective of this research is to develop an integrated Web-based distributed process planning system (Web-DPP) for job-shop machining operations and their runtime execution monitoring. Our approach tries to engage a dispersed working group in a collaborative environment, allowing the team members to share real-time information through the Web-DPP. This paper analyses the challenges, and presents both the system design specification and the latest development of the Web-DPP system. Particularly, it proposes a two-tier architecture for effective decision making and introduces a set of event-driven function blocks for bridging the gap between high-level planning and low-level execution functions. By connecting to a Wise-ShopFloor framework, it enables real-time execution monitoring during the machining operations, locally or remotely. The closed-loop information flow makes adaptive planning possible.

  • 11.
    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.

  • 12.
    Wang, Lihui
    et al.
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Givehchi, Mohammad
    University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
    Schmidt, Bernard
    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.
    Robotic Assembly Planning and Control with Enhanced Adaptability2012In: 45th CIRP Conference on Manufacturing Systems 2012 / [ed] G. Chryssolouris, D. Mourtzis, Elsevier, 2012, Vol. 3, p. 173-178Conference paper (Refereed)
    Abstract [en]

    The dynamic market today requires manufacturing companies to possess high degree of adaptability and flexibility in order to deal with shop-floor uncertainties. Such uncertainties as missing tools, part shortage, job delay, rush-order and unavailability of resources, etc. happen more often in assembly operations. Targeting this problem, this research proposes a function block enabled approach to achieving adaptability and flexibility in assembly planning and control. In particular, this paper presents our latest development using a robotic mini assembly cell for testing and validation of a function block enabled system capable of assembly and robot trajectory planning and control. It is expected that a better adaptability can be achieved by this approach.

  • 13.
    Wang, Lihui
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Department of Production Engineering, Royal Institute of Technology, Stockholm, Sweden.
    Schmidt, Bernard
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Givehchi, Mohammad
    Department of Production Engineering, Royal Institute of Technology, Stockholm, Sweden.
    Adamson, Göran
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Robotic Assembly Planning and Control with Enhanced Adaptability through Function Blocks2015In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 77, no 1-4, p. 705-715Article in journal (Refereed)
    Abstract [en]

    Manufacturing companies today need to maintain a high level of flexibility and adaptability to deal with uncertainties on dynamic shop floors, including e.g. cutting tool shortage, part supply interruption, urgent job insertion or delay, and machine unavailability. Such uncertainties are characteristic in component assembly operations. Addressing the problem, we propose a new method using function blocks to achieve much improved adaptability in assembly planning and robot control. In this paper, we propose to use event-driven function blocks for robotic assembly, aiming to plan trajectory and execute assembly tasks in real-time. It is envisioned that this approach will achieve better adaptability if applied to real-world applications.

1 - 13 of 13
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