liu.seSearch for publications in DiVA
Change search
Refine search result
1 - 9 of 9
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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.
    Feng, Xiaolong
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Management and Engineering, Machine Design.
    Sander- Tavalley, S.
    Ölvander, Johan
    Linköping University, The Institute of Technology. Linköping University, Department of Mechanical Engineering, Machine Design.
    Cycle-based Robot Drive Train Optimization Utilizing SVD Analysis2008In: ASME Design Automation Conference,2007, Las Vegas: ASME , 2008, p. 903-910Conference paper (Refereed)
    Abstract [en]

    Designing a drive train for an industrial robot is a demanding task where a set of design variables need to be determined so that optimal performance is obtained for a wide range of different duty cycles. The paper presents a method where singular value decomposition (SVD) is used to reduce the design variable set. The application is a six degree of freedom serial manipulator, with nine drive train parameters for each axis and the objective is to minimize the cycle time on 122 representative design cycles without decreasing the expected lifetime of the robot. The optimization is based on a simulation model of the robot and conducted on a reduced set of the initial duty cycles and with the design variables suggested by the SVD analysis. The obtained design reduces the cycle time with 1.6% on the original design cycles without decreasing the life time of the robot.

  • 2.
    Mandl, Clemens
    et al.
    University of Applied Sciences Technikum Wien, Vienna, Austria.
    Feng, Xiaolong
    ABB Corporate Research, Västerås, Sweden.
    Ölvander, Johan
    Linköping University, Department of Mechanical Engineering, Machine Design. Linköping University, The Institute of Technology.
    Automated Design of an Industrial Robot Family2009In: ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference: Volume 5: 35th Design Automation Conference, Parts A and B, New York, NY, USA: American Society of Mechanical Engineers, ASME , 2009, p. 927-939Conference paper (Refereed)
    Abstract [en]

    In this work, a methodology and an integrated tool framework has been developed for automated design of an industrial robot family consisting of four robot members. For each robot, performance requirements concerning payloads, reaches, and time performances are specified. A 3D design tool, namely Solid Works, has been integrated with robot kinematics and dynamics simulation tools for simultaneous kinematics and dynamics design. A motor library comprising both geometric data and physical data has also been integrated in the tool framework. The automated design of the robot family has been formulated as a multi-objective and mixed variable design optimization problem. The arm modules are treated as continuous design variables while the motors are treated as discrete variables. Due to the characteristics of this mixed variable design optimization problem a genetic algorithm (GA) has been used. This work has successfully demonstrated the feasibility for achieving automatic design of an industrial robot family.

  • 3.
    Persson, Johan
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Feng, Xiaolong
    ABB Corporate Research Västerås, Sweden.
    Wappling, Daniel
    ABB Corporate Research Västerås, Sweden.
    Ölvander, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    A Framework for Multidisciplinary Optimization ofa Balancing Mechanism for an Industrial Robot2015In: Journal of Robotics, ISSN 1687-9600, E-ISSN 1687-9619, p. 1-8, article id 389769Article in journal (Other academic)
    Abstract [en]

    The paper presents a framework that can be used to design and optimize a balancing mechanism for an industrial robot. The framework has the capability to optimize three different concepts - a mechanical, a pneumatic and a hydro-pneumatic. Several disciplines are included in the framework, such as dynamic and static analyses of the robot performance. Optimization is performed for each concept and the obtained optimal designs are all better then the reference design. This means that the framework can be used both as a tool to optimize the balancing mechanism and also to support concept selection.

  • 4.
    Pettersson, Marcus
    et al.
    Linköping University, Department of Management and Engineering, Machine Design . Linköping University, The Institute of Technology.
    Andersson (Ölvander), Johan
    Linköping University, Department of Management and Engineering, Machine Design . Linköping University, The Institute of Technology.
    Krus, Petter
    Linköping University, Department of Management and Engineering, Machine Design . Linköping University, The Institute of Technology.
    Wäppling, D.
    Feng, Xiaolong
    Linköping University, Department of Management and Engineering, Machine Design . Linköping University, The Institute of Technology.
    Industrial Robot Design Optimization in the Conceptual Design Phase2004In: Proceedings of IEEE International Conference on Mechatronics and Robotics, Aachen , Germany, 2004Conference paper (Other academic)
  • 5.
    Tarkian, Mehdi
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Persson, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Ölvander, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Feng, Xiaolong
    ABB Corporate Research, Västerås, Sweden.
    Multidisciplinary design optimization of modular Industrial Robots2011In: Proceedings of the ASME 2011 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, IDETC/CIE 2011, August 28- 31, 2011, Washington, DC, USA, The American Society of Mechanical Engineers (ASME) , 2011, Vol. 5, p. 867-876Conference paper (Refereed)
    Abstract [en]

    This paper presents a multidisciplinary design optimization framework for modular industrial robots. An automated design framework, containing physics based high fidelity models for dynamic simulation and structural strength analyses are utilized and seamlessly integrated with a geometry model.

    The proposed frameworkutilizes well-established methods such as metamodeling and multi-level optimization inorder to speed up the design optimization process. The contributionof the paper is to show that by applying amerger of well-established methods, the computational cost can be cutsignificantly, enabling search for truly novel concepts.

  • 6.
    Tarkian, Mehdi
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Persson, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Ölvander, johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Feng, Xiaolong
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Multidisciplinary Design Optimization of Modular Industrial Robots by Utilizing High Level CAD templates2012In: Journal of mechanical design (1990), ISSN 1050-0472, E-ISSN 1528-9001, Vol. 134, no 12Article in journal (Refereed)
    Abstract [en]

    This paper presents a multidisciplinary design optimization (MDO) framework for automated design of a modular industrial robot. The developed design framework seamlessly integrates High Level CAD templates (HLCt) and physics based high fidelity models for automated geometry manipulation, dynamic simulation, and structural strengthanalysis. In the developed framework, methods such as surrogate models and multilevel optimization are employed in order to speed up the design optimization process. This work demonstrates how a parametric geometric model, based on the concept of HLCt, enables a multidisciplinary framework for multi-objective optimization of a modular industrial robot, which constitutes an example of a complex heterogeneous system.

  • 7.
    Tarkian, Mehdi
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Vemula, Bhanoday
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Feng, Xiaolong
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Ölvander, johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Metamodel Based Design Automation – Applied on Multidisciplinary Design Optimization of Industrial Robots2012In: Proceedings of the ASME InternationalDesign Engineering Technical Conferences & Computers and information in Engineering Conference,Washington, USA, Aug 2012, 2012, p. 833-845Conference paper (Other academic)
    Abstract [en]

    Intricate and complex dependencies between multiple disciplines require iterative intensive optimization processes. To this end, multidisciplinary design optimization (MDO) has been established as a convincing concurrent technique to manage inherited complexities.

    This paper presents a high level CAD and CAE design automation methodology which enables fast, efficient concept generation for MDO. To increase the evaluation speed, global metamodels are introduced to replace computationally expensive CAD and CAE models. In addition, various techniques are applied to drastically decrease the number ofsamplings required to create the metamodels. In the final part of the paper, a multi-level optimization strategy is proposed to find the optimal concept.

    As proof of concept, a real world design problem, from ABB industrial robotics, is presented.

  • 8.
    Tarkian, Mehdi
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    ölvander, johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Feng, Xiaolong
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Pettersson, Marcus
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Product Platform Automation for Optimal Configuration of Industrial Robot Families2011In: Proceedings of the 18th International Conference on Engineering Design (ICED11), Vol. 4, 2011, p. 1-10Conference paper (Refereed)
    Abstract [en]

    Product platform design is a well recognized methodology to effectively increase range and variety of products and simultaneously decrease internal variety of components by utilizing modularization. The tradeoff between product performance and product family commonality has to be carefully balanced in order to for the company to meet market requirements and simultaneously obtain economy of scale. This paper presents a framework based on high fidelity analyses tools that concurrently optimize an industrial robot family as well as the common platform. The product family design problem is formally stated as a multi-objective optimization problem, which is solved using a multi-objective Genetic Algorithm.

  • 9.
    Ölvander, Johan
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Tarkian, Mehdi
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Feng, Xiaolong
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Multi-objective Optimization of a family of Industrial Robots2011In: Multi-objective Evolutionary Optimisation for Product Design and Manufacturing / [ed] Wang L., Ng A. H.C., Deb K., Springer Verlag , 2011, p. 189-217Chapter in book (Refereed)
    Abstract [en]

    With the increasing complexity and dynamism in today’s product design and manufacturing, more optimal, robust and practical approaches and systems are needed to support product design and manufacturing activities. Multi-objective Evolutionary Optimisation for Product Design and Manufacturing presents a focused collection of quality chapters on state-of-the-art research efforts in multi-objective evolutionary optimisation, as well as their practical applications to integrated product design and manufacturing. Multi-objective Evolutionary Optimisation for Product Design and Manufacturing consists of two major sections. The first presents a broad-based review of the key areas of research in multi-objective evolutionary optimisation. The second gives in-depth treatments of selected methodologies and systems in intelligent design and integrated manufacturing. Recent developments and innovations in multi-objective evolutionary optimisation make Multi-objective Evolutionary Optimisation for Product Design and Manufacturing a useful text for a broad readership, from academic researchers to practicing engineers.

1 - 9 of 9
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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