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Design Optimization in Industrial Robotics: Methods and Algorithms for Drive Train Design
Linköping University, Department of Management and Engineering, Machine Design . Linköping University, The Institute of Technology.
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Robot manufacturers, like many other manufacturers, are experiencing increasing competition in a global market where one way to confront the challenge is by making the development process more efficient. One way to speed up the time to market for new products is to take advantage of design optimization based on simulation models. By optimizing performance with the help of dynamic simulation, an immense amount of both time and money may be saved.

In this thesis, design optimization strategies for industrial robot design are studied. Often, the trade-offs between performance, cost and quality are essential for design decisions. These tradeoffs can be investigated with the help of simulation models. Generating the trade-offs can be both cumbersome and time-consuming, but the process may be partly automated with the help of optimization algorithms. How the optimization problem needs to be formulated to generate the trade-off is discussed in this thesis.

Robot design problems usually consist of a mixture of deciding continuous parameters as well as selecting components from catalogs and databases. Hence, there is a need for optimization algorithms which can handle variables of both a discrete and a continuous nature. A new method has been developed to address this problem. The method has also been improved by adding adaptive characteristics for further efficient design optimization.

The ideas in this thesis have been applied to both simulation models of conceptual degrees of elaboration as well as simulation models of complete robot systems. An optimization procedure which shows how optimization can be used in the early phases of a development process is developed. The objective of the optimization is to determine optimal gearboxes and arm lengths from an acceleration capability perspective. An optimization based design method for robot drive trains is also presented. For further efficient use of already installed robots the concept of application adapted performance optimization is introduced. This means that the robot control is optimized with respect to thermal and fatigue load for the specific program that the robot performs. The motion program itself, i.e. the path planning, can be optimized at the same time in order to get the most out of the robot.

Place, publisher, year, edition, pages
Institutionen för ekonomisk och industriell utveckling , 2008. , 81 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1170
Keyword [en]
Robot manufacturers, industrial robot, robot design
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:liu:diva-11664ISBN: 978-91-7393-945-4 (print)OAI: oai:DiVA.org:liu-11664DiVA: diva2:18090
Public defence
2008-04-25, C3, Hus C, Campus Valla, Linköpings universitet, Linköping, 10:15 (English)
Opponent
Supervisors
Available from: 2008-04-28 Created: 2008-04-28 Last updated: 2009-05-12
List of papers
1. Industrial Robot Design Optimization in the Conceptual Design Phase
Open this publication in new window or tab >>Industrial Robot Design Optimization in the Conceptual Design Phase
Show others...
2004 (English)In: Proceedings of IEEE International Conference on Mechatronics and Robotics, Aachen , Germany, 2004Conference paper, Published paper (Other academic)
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-13228 (URN)
Available from: 2008-04-28 Created: 2008-04-28 Last updated: 2009-05-29
2. Methods for Discrete Design Optimization
Open this publication in new window or tab >>Methods for Discrete Design Optimization
2005 (English)In: Proceedings of ASME 31st Design Automation Conference, September 24-28, Long Beach, USA, 2005Conference paper, Published paper (Other academic)
Abstract [en]

One area in design optimization is component based design where the designer has to choose between many different discrete alternatives. These types of problems have discrete character and in order to admit optimization an interpolation between the alternatives is often performed. However, in this paper a modified version of the non-gradient algorithm the Complex method is developed where no interpolation between alternatives is needed. Furthermore, the optimization algorithm itself is optimized using a performance metric that measures the effectiveness of the algorithm. In this way the optimal performance of the proposed discrete Complex method has been identified. Another important area in design optimization is the case of optimization based on simulations. For such problems no gradient information is available, hence non-gradient methods are therefore a natural choice. The application for this paper is the design of an industrial robot where the system performance is evaluated using comprehensive simulation models. The objective is to maximize performance with constraints on lifetime and cost, and the design variables are discrete choices of gear boxes for the different axes.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-13229 (URN)
Available from: 2008-04-28 Created: 2008-04-28 Last updated: 2009-05-29
3. On Optimal Drive Train Design in Industrial Robots
Open this publication in new window or tab >>On Optimal Drive Train Design in Industrial Robots
2005 (English)In: Proceedings of IEEE International Conference on Industrial Technology, Hong Kong, December 2005, 2005, 254-259 p.Conference paper, Published paper (Other academic)
Abstract [en]

In this paper optimization is used to determine which gearboxes to use in an industrial robot. The paper also presents a procedure where tradeoff information is generated based on consecutive optimizations. Thereby the method provides the designer with information about critical tradeoffs between conflicting objectives. This type of information is very valuable when negotiating between different design alternatives. Generating these tradeoffs is traditionally a time consuming process, but by introducing optimization this process can be partly automated. The design variables studied are composed of continuous and discrete parameters, where the latter are associated with different gearbox alternatives and the continuous variables with the speed-torque limitation of the gearboxes. A non-gradient based optimization algorithm which can handle mixed variables problems is used to solve the highly non-linear problem. The outcome from an industrial point of view is minimization of cost and simultaneously balance the trade-off between lifetime and performance.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-13230 (URN)10.1109/ICIT.2005.1600645 (DOI)
Available from: 2008-04-28 Created: 2008-04-28 Last updated: 2009-05-29
4. A Component Based Optimization Approach for Robot Modular Design
Open this publication in new window or tab >>A Component Based Optimization Approach for Robot Modular Design
2007 (English)In: Proceedings of DETC'2007 ASME Design Automation Conference, September, Las Vegas, Nevada, USA, 2007Conference paper, Published paper (Other academic)
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-13231 (URN)
Available from: 2008-04-28 Created: 2008-04-28 Last updated: 2009-03-25
5. Application Adapted Performance Optimization for Industrial Robots
Open this publication in new window or tab >>Application Adapted Performance Optimization for Industrial Robots
2007 (English)In: IEEE International Symposium on Industrial Electronics, 4-7 June 2007, Vigo, Spain, 2007, 2047-2052 p.Conference paper, Published paper (Other academic)
Abstract [en]

Industrial robots are designed for a large spectrum of user scenarios. This implies that the robot cannot be tailor made for each situation and hence its full potential might not always be fully exploited. For further efficient use of robots the concept of application adapted performance optimization is introduced. This means that the robot control is optimized with respect to thermal and fatigue load for the specific program, which the robot performs. Simultaneously the motion program itself i.e. the path planning can be optimized in order to get the most out of the robot. These ideas are tested on a six axis robot in a press tending application.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-13232 (URN)10.1109/ISIE.2007.4374923 (DOI)
Available from: 2008-04-28 Created: 2008-04-28 Last updated: 2009-03-16
6. Adaptive Complex Method for Efficient Design Optimization
Open this publication in new window or tab >>Adaptive Complex Method for Efficient Design Optimization
2007 (English)In: Proceedings of ASME 33rd Design Automation Conference, September 4-7, Las Vegas, USA, 2007, 265-272 p.Conference paper, Published paper (Other academic)
Abstract [en]

Box’s Complex method for direct search has shown promise when applied to simulation based optimization. In direct search methods, like Box’s Complex method, the search starts with a set of points, where each point is a solution to the optimization problem. In the Complex method the number of points must be at least one plus the number of variables. However, in order to avoid premature termination and increase the likelihood of finding the global optimum more points are often used at the expense of the required number of evaluations. The idea in this paper is to gradually remove points during the optimization in order to achieve an adaptive Complex method for more efficient design optimization. The proposed method shows encouraging results when compared to the Complex method with fix number of points and a quasi-Newton method.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-13233 (URN)10.1115/DETC2007-34773 (DOI)0-7918-3806-4 (ISBN)0-7918-4807-8 (ISBN)
Conference
ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
Available from: 2008-04-28 Created: 2008-04-28 Last updated: 2014-08-21
7. Drive Train Optimization for Industrial Robots
Open this publication in new window or tab >>Drive Train Optimization for Industrial Robots
2008 (English)In: IEEE Transactions on RoboticsArticle in journal (Refereed) Submitted
Identifiers
urn:nbn:se:liu:diva-13234 (URN)
Available from: 2008-04-28 Created: 2008-04-28 Last updated: 2010-04-23

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