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A Framework for Multidisciplinary Optimization ofa Balancing Mechanism for an Industrial Robot
Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
ABB Corporate Research Västerås, Sweden.
ABB Corporate Research Västerås, Sweden.
Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
2015 (English)In: Journal of Robotics, ISSN 1687-9600, E-ISSN 1687-9619, 1-8 p., 389769Article in journal (Other academic) Published
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.

Place, publisher, year, edition, pages
Hindawi Publishing Corporation, 2015. 1-8 p., 389769
Keyword [en]
Industrial Robots, Optimization, Multi-Disciplinary, Optimization
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:liu:diva-115938DOI: 10.1155/2015/389769ISI: 000361964900001OAI: oai:DiVA.org:liu-115938DiVA: diva2:797556
Note

At the time of the thesis presentation this publication was in status Manuscript.

Available from: 2015-03-24 Created: 2015-03-24 Last updated: 2017-12-04Bibliographically approved
In thesis
1. Efficient Optimization of Complex Products: A Simulation and Surrogate Model Based Approach
Open this publication in new window or tab >>Efficient Optimization of Complex Products: A Simulation and Surrogate Model Based Approach
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis investigates how to use optimization efficiently when complex products are developed. Modelling and simulation are necessary to enable optimization of products, but here it is assumed that verified and validated models of the products and their subsystems are available for the optimization. The focus is instead on how to use the models properly for optimization.

Knowledge about several areas is needed to enable optimization of a wide range of products. A few methods from each area are investigated and compared. Some modifications to existing methods and new methods are also proposed and compared to the previous methods.

These areas include

  • Optimization algorithms to ensure that a suitable algorithm is used to solve the problem
  • Multi-Objective Optimization for products with conflicting objectives
  • Multi-Disciplinary Optimization when analyses from several models and/or disciplines are needed
  • Surrogate Models to enable optimization of computationally expensive models

Modern frameworks for optimization of complex products often include more than one of these areas and this is exemplified with the industrial applications that are presented in this thesis, including the design and optimization of industrial robots and aircraft systems.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2015. 88 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1655
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:liu:diva-115939 (URN)10.3384/diss.diva-115939 (DOI)978-91-7519-083-9 (ISBN)
Public defence
2015-04-24, ACAS, A-huset, Campus Valla, Linköping, 10:15 (English)
Opponent
Supervisors
Funder
EU, FP7, Seventh Framework Programme, Crescendo no. 234244VINNOVA, IMPOz no. 2013-03758
Available from: 2015-03-24 Created: 2015-03-24 Last updated: 2015-04-17Bibliographically approved

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Persson, JohanFeng, XiaolongÖlvander, Johan

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