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  • 51.
    Persson, Johan
    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.
    Comparisons of Different Methods for Robust Optimization in Engineering DesignManuscript (preprint) (Other academic)
    Abstract [en]

    This paper compares the performance of five methods for robust design optimization of computationally demanding models including one novel method. The comparison is made using several mathematical functions and two engineering problems. The performance metrics are the mean value and standard deviation of the optimum as well as an index that weights together the required number of simulations of the original model and the chance of finding the optimum. The result of the comparison shows that sequential robust optimization is the most effective method.

  • 52.
    Persson, Johan
    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.
    Optimization of the Complex-RFM Optimization Algorithm2015In: Optimization and Engineering, ISSN 1389-4420, E-ISSN 1573-2924, Vol. 16, no 1, p. 27-48Article in journal (Refereed)
    Abstract [en]

    This paper presents and compares different modifications made to the Complex-RF optimization algorithm with the aim of improving its performance for computationally expensive models. The modifications reduces the required number of objective function evaluations by creating and using surrogate models of the objective function iteratively during the optimization process. The chosen surrogate model type is a second order response surface. The performance of the modified algorithm is compared with a number of existing algorithms and demonstrated for a few analytical and engineering problems.

  • 53.
    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.
    Methods for Discrete Design Optimization2005In: Proceedings of ASME 31st Design Automation Conference, September 24-28, Long Beach, USA, 2005Conference 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.

  • 54.
    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.
    On Optimal Drive Train Design in Industrial Robots2005In: Proceedings of IEEE International Conference on Industrial Technology, Hong Kong, December 2005, 2005, p. 254-259Conference 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.

  • 55.
    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)
  • 56.
    Pettersson, Marcus
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Ölvander Andersson, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Adaptive Complex Method for Efficient Design Optimization2007In: Proceedings of ASME 33rd Design Automation Conference, September 4-7, Las Vegas, USA, 2007, p. 265-272Conference 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.

  • 57.
    Pettersson, Marcus
    et al.
    Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology.
    Ölvander (Andersson), Johan
    Linköping University, The Institute of Technology.
    Drive Train Optimization for Industrial Robots2008In: IEEE Transactions on RoboticsArticle in journal (Refereed)
  • 58.
    Pettersson, Marcus
    et al.
    Linköping University, Department of Management and Engineering, Machine Design . Linköping University, The Institute of Technology.
    Ölvander Andersson, Johan
    Linköping University, Department of Management and Engineering, Machine Design . Linköping University, The Institute of Technology.
    Andersson, Henric
    Linköping University, Department of Management and Engineering, Machine Design . Linköping University, The Institute of Technology.
    Application Adapted Performance Optimization for Industrial Robots2007In: IEEE International Symposium on Industrial Electronics, 4-7 June 2007, Vigo, Spain, 2007, p. 2047-2052Conference 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.

  • 59.
    Pettersson, Marcus
    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.
    Drive Train Optimization for Industrial Robots2009In: IEEE TRANSACTIONS ON ROBOTICS, ISSN 1552-3098, Vol. 25, no 6, p. 1419-1424Article in journal (Refereed)
    Abstract [en]

    This paper presents an optimization strategy for finding the trade-offs between cost, lifetime, and performance when designing the drive train, i.e., gearboxes and electric motors, for new robot concepts. The method is illustrated with an example in which the drive trains of two principal axes on a six-axis serial manipulator are designed. Drive train design for industrial robots is a complex task that requires a concurrent design approach. For instance, the mass properties of one motor affect the torque requirements for another, and the method needs to consider several drive trains simultaneously. Since the trajectory has a large impact on the load on the actuators when running a robot, the method also includes the trajectory generation itself in the design loop. It is shown how the design problem can be formalized as an optimization problem. A non-gradient-based optimization algorithm that can handle mixed variable problems is used to solve the highly nonlinear problem. The outcome from an industrial point of view is minimization of cost and the simulataneous balancing of the trade-off between lifetime and performance.

  • 60.
    Pettersson, Marcus
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Mechanical Engineering, Machine Design.
    Ölvander, Johan
    Linköping University, The Institute of Technology. Linköping University, Department of Mechanical Engineering, Machine Design.
    Andersson, Henric
    Linköping University, The Institute of Technology. Linköping University, Department of Mechanical Engineering, Machine Design.
    Adaptive Performance for Industrial Robotics2007In: IEEE International Symposium on Industrial Electronics,2007, Vigo, Spain: IEEE , 2007Conference paper (Refereed)
  • 61.
    Safavi, Edris
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Chaitanya, Raghu
    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.
    Krus, Petter
    Linköping University, Department of Management and Engineering, Fluid and Mechatronic Systems. Linköping University, The Institute of Technology.
    Multidisciplinary Optimization of Aircraft Vehicle System for Conceptual Analysis2013In: , Aerospace Research Central, ARC , 2013, p. 1-9Conference paper (Other academic)
    Abstract [en]

    An aircraft is a multifaceted product which requires cooperation between different engineering domains. Therefore, design of an aircraft is essentially a multidisciplinary activity with necessity of integrating dierent design tools to get an optimized product. At Linkoping University, a design framework is being developed to assist in the evaluation and optimization of various aircraft vehicle system architectures with the help of integrating a geometric, aerodynamic and dynamic models early in the conceptual design phase. This framework helps to identify a preliminary system concept for an energy optimized aircraft architecture with the focus on more electrical aircraft. As a case study the performance and geometrical aspects of an EMA (Electromechanical actuator) are evaluated and optimized.

  • 62.
    Safavi, Edris
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Gopinath, Varun
    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.
    Gavel, Hampus
    SAAB AB, Sweden.
    A Collaborative Tool for Conceptual Aircraft Systems Design2012In: Guidance, Navigation, and Control and Co-located Conferences: AIAA Modeling and Simulation Technologies Conference / [ed] The American Institute of Aeronautics and Astronautics, Reston, VA, USA: American Institute of Aeronautics and Astronautics, 2012, p. 1-10Conference paper (Refereed)
    Abstract [en]

    Advances in recent years has brought forth many feasible technologies which oer signif-icant design advantages over the traditional aircraft vehicle ight systems. These advanceshave brought about a need for the aircraft conceptual engineers to evaluate these newtechnologies so as to realize a realistic and optimized architecture which fulls all criti-cal disciplinary requirements. To evaluate these systems, it is necessary to use models ofcomplexity which are a degree higher than what is being used today. Quick developmentand evaluation of these models can be a hard task for an engineer to achieve consideringthe multidisciplinary nature of the systems. A collaborative eort in model developmentbetween various department is needed if the conceptual design is to be completed withinthe time frame. To facilitate a collaborative conceptual design a research project was for-malized at Linkoping university, which has led to the development of a tool named CAVE(Conceptual Aircraft Vehicle Engineering) which can be used to evaluate the architectureof aircraft systems. In this paper, CAVE as a conceptual design tool will be presented.

  • 63.
    Safavi, Edris
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Gopinath, Varun
    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.
    Gavel, Hampus
    SAAB AB, Sweden.
    Conceptual Optimization of Aircraft Actuator Systems2012In: Proceedings of the International Conference on recent advances in aerospace actuation systems and components, Toulouse, France: Institut national des sciences appliquées , 2012, p. 201-Conference paper (Other academic)
    Abstract [en]

    The aim of this research project is to identify a preliminary architecture of a flight control actuation system concept for energy optimized aircraft system architecture with the focus on more electrical aircraft. At Linköping University a design framework is being developed to assist in the evaluation of aircraft flight system at a conceptual level using dynamic models which has led to the development of a tool named CAVE.

    In this paper the use of the framework to approach the problem of finding a suitable flight actuator system for a number of flight control surfaces distributed over the aircraft with different boundary conditions (maximum torque and flap deflection) is presented. Dynamic models for three of the most commonly used actuation technologies have been developed in Dymola and each system has been optimized with mass and energy consumption as the objectives.

  • 64.
    Safavi, Edris
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Namakian, Mohsen
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Sirén, Tim
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Magnéli, Rickard
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Ölvander, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Design and Evaluation of Airborne Wind Turbine Utilizing Physical Prototype2013In: International Congress on Energy Efficiency and Energy Related Materials (ENEFM2013): Proceedings, Antalya, Turkey, 9-12 October 2013 / [ed] Ahmet Yavuz Oral, Zehra Banu Bahsi, Mehmet Ozer, Springer, 2013, 1, p. 57-64Chapter in book (Other academic)
    Abstract [en]

    Moving towards renewable sources of energy has become one of the most important energy-related strategies in recent decades. High-altitude wind power (HAWP) has been discovered in 1833 as a source of useful energy. Wind power density (Watts/m2)  can significantly increase (~6 times) by going from 80 to 500 m altirude The global capacity of 380 TW (terawau) as well as abundance, strength, and relative persistency of wind in higher altitude are eye-catch ing poinls to consider HAWP as a reliable energy source in the future. A research project called "THOR" has been initiated at Linköping University by a group of master students (soon to graduate) as proof of concept of airborne wind energy (AWES). THOR is about feasibility analysis of different concepts of HAWP and proof of concept of balloon based AWES as one of the appropriate existing concepts. THOR is intended to be a research platform at Linköping University for further development of AWES concepts i n future.

  • 65.
    Safavi, Edris
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Tarkian, Mehdi
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Gavel, Hampus
    SAAB, Department Modeling and Simulat Vehicle Syst, Linkoping, Sweden.
    Ölvander, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Collaborative multidisciplinary design optimization: A framework applied on aircraft conceptual system design2015In: Concurrent Engineering - Research and Applications, ISSN 1063-293X, E-ISSN 1531-2003, Vol. 23, no 3, p. 236-249Article in journal (Refereed)
    Abstract [en]

    In a product development process, it is crucial to understand and evaluate multiple and synergic aspects of systems such as performance, cost, reliability, and safety. These aspects are mainly considered during later stages of the design process. However, in order to improve the foundations for decision-making, this article presents methods that are intended to increase the engineering knowledge in the early design phases. In complex products, different systems from a multitude of engineering disciplines have to work tightly together. Collaborative design is described as a process where a product is designed through the collective and joint efforts of domain experts. A collaborative multidisciplinary design optimization process is therefore proposed in the conceptual design phase in order to increase the likelihood of more accurate decisions being taken early on. The performance of the presented framework is demonstrated in an industrial application to design aircraft systems in the conceptual phase.

  • 66.
    Safavi, Edris
    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.
    Ölvander, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Rapid Concept Realization for Conceptual Design of Modular Industrial Robots2010In: Proceedings of NordDesign 2010, the 8th International NordDesign Conference, Göteborg, Sweden, 25.-27.08. 2010 / [ed] Andreas Dagman and Rikard Söderberg, 2010, p. 375-384Conference paper (Refereed)
    Abstract [en]

    When conducting design on novel mechatronic products, it can be valuable to test and evaluate the performance and properties of the concepts throughout the design process by producing them as downscaled prototypes, see Jouannet et al. [1]. This is especially true when the product is of unconventional design and the designer can get increased confidence of the proposed concept by testing it as a sub scaled version. Nonetheless, the process of realization of new concept should be done in a rapid fashion in order not to halt the design process and simultaneously increasing explicit knowledge about the concept. A case study will be illustrated which demonstrates how fully automated design and construction of downscaled prototypes is performed.

  • 67.
    Sharifimajd, Babak
    et al.
    Institute of Solid Mechanics, Department of Mechanical Engineering, Braunschweig University of Technology, Braunschweig, Germany.
    Ölvander, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Stålhand, Jonas
    Linköping University, Department of Management and Engineering, Solid Mechanics. Linköping University, Faculty of Science & Engineering.
    Identification of the mechanical parameters for the human uterus in vivo using intrauterine pressure measurements2017In: International Journal for Numerical Methods in Biomedical Engineering, ISSN 2040-7939, E-ISSN 2040-7947, Vol. 33, no 1, p. 1-11Article in journal (Refereed)
    Abstract [en]

    There are limited experimental data to characterize the mechanical response of human myometrium. A method is presented in this work to identify mechanical parameters describing the active response of human myometrium from the in vivo intrauterine pressure measurements. A finite element model is developed to compute the intrauterine pressure during labor in response to an increase in the intracellular calcium ion concentration within myometrial smooth muscle cells. The finite element model provides the opportunity to tune mechanical parameters in order to fit the computed intrauterine pressure to in vivo measurements. Since the model is computationally expensive, a cheaper meta-model is generated to approximate the model response. By fitting the meta-model response to the in vivo measurements, the parameters used to determine the active response of human myometrial smooth muscle are identified.

  • 68.
    Tarkian, Mehdi
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Lundén, Björn
    ABB Corporate Research, Västerås, Sweden.
    Ölvander, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Integration of Parametric CAD and Dynamic Models for Industrial Robot Design and Optimization2009In: Volume 3: 28th Computers and Information in Engineering Conference: Parts A and B, New York City, New York, USA: American Society of Mechanical Engineers (ASME) , 2009, p. 761-769Conference paper (Refereed)
    Abstract [en]

    This paper presents an approach of integration between multiple analysis tools that covers several engineering disciplines, used for robot design and optimization. There are three main components in this approach namely a highly flexible geometric model, a parametric dynamic simulation model, and a framework for integration of the models and execution of an optimization process through a user friendly interface. To illustrate the presented methodology an integrated analysis tool for an industrial robot is developed combining dynamic and geometric models in a parametric design approach. An optimization case is conducted to visualize the automation capabilities of the proposed framework, and enhance the early design phases for industrial robots.

  • 69.
    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.

  • 70.
    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.

  • 71.
    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.

  • 72.
    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.
    Berry, Patrick
    Linköping University, Department of Mechanical Engineering, Fluid and Mechanical Engineering Systems. Linköping University, The Institute of Technology.
    Exploring Parametric CAD-models in Aircraft Conceptual Design2008In: 49th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 2008, Reston, VA, USA: American Institute of Aeronautics and Astronautics, 2008Conference paper (Other academic)
    Abstract [en]

    The ever fast growing information technology is enabling the re-definition of early stages of aircraft design which have been restricted mostly by statistical and empirical approaches because of lengthy and costly simulation times. This paper will describe a methodology based on parametric and generic CAD modeling methods which will save time when performing repetitive tasks automatically. Furthermore, it enables greater comprehension by giving a holistic view of the aircraft systems because of the proposed multidisciplinary and modular framework. The framework involves a centralized easy to use interface which is coupled to a series of analyses tools. The proposed methods have been applied in student projects of the course -Aircraft Conceptual Design- from Linköping University where it has shown great promises.

  • 73.
    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
    ABB Corporate Research, Västerås.
    Pettersson, Marcus
    ABB Corporate Research, Västerås.
    Design Automation of Modular Industrial Robots2009In: ASME CIE09, San Diego, USA, Sep. 2009, 2009, p. 655-664Conference paper (Other academic)
    Abstract [en]

    This paper presents a novel approach for designing modular robots. There are two main components in this approach namely the modeling methodology of the robot and a framework for simulation of the models and execution of an optimization process.

    To illustrate the presented methodology an integrated analysis tool for an industrial robot is developed combining dynamic and geometric models in a parametric design approach. An optimization case is conducted to visualize the automation capabilities of the proposed framework, and enhance the design for modular industrial robots.

  • 74.
    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.

  • 75.
    Wiberg, Anton
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Andersson (Ölvander), Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Design for Additive Manufacturing using a Master Model approach2019Conference paper (Refereed)
  • 76.
    Wiberg, Anton
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Persson, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Ölvander, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    AN OPTIMIZATION FRAMEWORK FOR ADDITIVE MANUFACTURING GIVEN TOPOLOGY OPTIMIZATION RESULTS2018In: Tools and Methods of Competitive Engineering: Implementation, application and utilization of smart systems, 2018Conference paper (Other academic)
    Abstract [en]

    In this paper, a method of designing for Additive Manufacturing (AM) is proposed, implemented, and evaluated in a case study. In the proposed method, Topological Optimization is combined with a Multidisciplinary Design Optimization (MDO) framework that handles multi-objective optimization. Both the weight and amount of support material needed during manufacturing are minimized. In the proposed method, the topological optimized structure is remodelled into a parametric CAD model. The CAD model is then combined with an FE-model that calculates the stresses in the material and a model that calculates the amount of support structure needed. Two different optimization formulations are evaluated and compared in the case study.

    In the case study an upright of a Formula Student racing car is designed. Several design evaluations are performed resulting in a set of Pareto optimal designs that could be used for decision-making where the trade-off between the two objectives is considered. It is concluded that the proposed method fulfils its purpose by being able to identify designs that would be difficult to come up with manually. Several suggestions for further studies in order to improve the method are also discussed.

  • 77.
    Wiberg, Anton
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Persson, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Ölvander, Johan
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, Faculty of Science & Engineering.
    Design for additive manufacturing: a review of available design methods and software2019In: Rapid prototyping journal, ISSN 1355-2546, E-ISSN 1758-7670, Vol. 25, no 6, p. 15p. 1080-1094Article, review/survey (Refereed)
    Abstract [en]

    Purpose

    This paper aims to review recent research in design for additive manufacturing (DfAM), including additive manufacturing (AM) terminology, trends, methods, classification of DfAM methods and software. The focus is on the design engineer’s role in the DfAM process and includes which design methods and tools exist to aid the design process. This includes methods, guidelines and software to achieve design optimization and in further steps to increase the level of design automation for metal AM techniques. The research has a special interest in structural optimization and the coupling between topology optimization and AM.

    Design/methodology/approach

    The method used in the review consists of six rounds in which literature was sequentially collected, sorted and removed. Full presentation of the method used could be found in the paper.

    Findings

    Existing DfAM research has been divided into three main groups – component, part and process design – and based on the review of existing DfAM methods, a proposal for a DfAM process has been compiled. Design support suitable for use by design engineers is linked to each step in the compiled DfAM process. Finally, the review suggests a possible new DfAM process that allows a higher degree of design automation than today’s process. Furthermore, research areas that need to be further developed to achieve this framework are pointed out.

    Originality/value

    The review maps existing research in design for additive manufacturing and compiles a proposed design method. For each step in the proposed method, existing methods and software are coupled. This type of overall methodology with connecting methods and software did not exist before. The work also contributes with a discussion regarding future design process and automation.

  • 78.
    Zachrison, Anders
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Mechanical Engineering, Fluid and Mechanical Engineering Systems.
    Rösth, Marcus
    Linköping University, The Institute of Technology. Linköping University, Department of Mechanical Engineering, Fluid and Mechanical Engineering Systems.
    Ölvander, Johan
    Linköping University, The Institute of Technology. Linköping University, Department of Mechanical Engineering, Machine Design.
    Werndin, Ronnie
    Linköping University, The Institute of Technology. Linköping University, Department of Mechanical Engineering, Fluid and Mechanical Engineering Systems.
    Evolve - A Vehicle Based Test Platform for Active Rear Axle Camber and Steering Control2003In: SAE 2003 World Congress,2003, Detroit, USA: SAE , 2003Conference paper (Refereed)
  • 79.
    Zachrison, Anders
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Mechanical Engineering, Fluid and Mechanical Engineering Systems.
    Rösth, Marcus
    Linköping University, The Institute of Technology. Linköping University, Department of Mechanical Engineering, Fluid and Mechanical Engineering Systems.
    Ölvander, Johan
    Linköping University, The Institute of Technology. Linköping University, Department of Mechanical Engineering, Machine Design.
    Werndin, Ronnie
    IKP Tekniska fakulteten.
    Evolve-A Vehicle-Based Test Platform for Active Rear Axle Camber and Steering Control2003In: SAE Transactions, ISSN 0096-736X, Vol. 112, no 6, p. 690-695Article in journal (Refereed)
  • 80.
    Ölvander, Johan
    Linköping University, The Institute of Technology. Linköping University, Department of Management and Engineering, Machine Design.
    Design of Fluid Power Systems Using a Multi-Objective Genetic Algorithm2004In: Applications of Multi-Objective Evolutionary Algorithms / [ed] Carlos A. Coello Coello, Gary B. Lamont, Singapore: World Scientific , 2004, p. -761Chapter in book (Other academic)
    Abstract [en]

    This book presents an extensive variety of multi-objective problems across diverse disciplines, along with statistical solutions using multi-objective evolutionary algorithms (MOEAs). The topics discussed serve to promote a wider understanding as well as the use of MOEAs, the aim being to find good solutions for high-dimensional real-world design applications. The book contains a large collection of MOEA applications from many researchers, and thus provides the practitioner with detailed algorithmic direction to achieve good results in their selected problem domain.

  • 81.
    Ölvander, Johan
    Linköping University, The Institute of Technology. Linköping University, Department of Management and Engineering, Machine Design .
    Robustness considerations in multi-objective optimal design2005In: Journal of engineering design (Print), ISSN 0954-4828, E-ISSN 1466-1837, Vol. 16, no 5, p. 511-523Article in journal (Refereed)
    Abstract [en]

    In real-world engineering design problems we have to search for solutions that simultaneously optimize a wide range of different criteria. Furthermore, the optimal solutions also have to be robust. Therefore, this paper presents a method where a multi-objective genetic algorithm is combined with response surface methods in order to assess the robustness of the identified optimal solutions. The design example is two different concepts of hydraulic actuation systems, which have been modelled in a simulation environment to which an optimization algorithm has been coupled. The outcome from the optimization is a set of Pareto optimal solutions that elucidate the trade-off between energy consumption and control error for each system. Based on these Pareto fronts, promising regions could be identified for each concept. In these regions, sensitivity analyses are performed and thus it can be determined how different design parameters affect the system at different optimal solutions.

  • 82.
    Ölvander, Johan
    Linköping University, The Institute of Technology. Linköping University, Department of Management and Engineering, Machine Design.
    Sensitivity Analysis in Multi-objective Evolutionary Design, in Recent Advances in Simulated Evolution and Learning2004In: Recent Advances in Simulated Evolution and Learning / [ed] K. C. Tan, Singapore: World Scientific series on Advances in Natural Computation , 2004, 2, p. -832Chapter in book (Other academic)
    Abstract [en]

          Inspired by the Darwinian framework of evolution through natural selection and adaptation, the field of evolutionary computation has been growing very rapidly, and is today involved in many diverse application areas. This book covers the latest advances in the theories, algorithms, and applications of simulated evolution and learning techniques. It provides insights into different evolutionary computation techniques and their applications in domains such as scheduling, control and power, robotics, signal processing, and bioinformatics. The book will be of significant value to all postgraduates, research scientists and practitioners dealing with evolutionary computation or complex real-world problems

  • 83.
    Ölvander, Johan
    et al.
    Linköping University, Department of Management and Engineering, Machine Design. Linköping University, The Institute of Technology.
    Feng, X.
    ABB Corporate Research, Västerås, Sweden.
    Holmgren, B.
    ABB Corporate Research, Västerås, Sweden.
    Optimal kinematics design of an industrial robot family in 2008 Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC 2008, vol 1, issue PART B, pp 777-7872009In: ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference: Volume 1: 34th Design Automation Conference, Parts A and B, The American Society of Mechanical Engineers (ASME) , 2009, Vol. 1, no PART B, p. 777-787Conference paper (Refereed)
    Abstract [en]

    Product family design is a well recognized method to address the demands of mass customization. A potential drawback of product families is that the performance of individual members are reduced due to the constraints added by the common platform, i.e. parts and components need to be shared by other family members. This paper presents a formal mathematical framework where the product family design problem is stated as an optimization problem and where optimization is used to find an optimal product family. The object of study is kinematics design of a family of industrial robots. The robot is a serial manipulator where different robots share arms from a common platform. The objective is to show the trade-off between the size of the common platform and the kinematics performance of the robot.

  • 84.
    Ölvander, Johan
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Management and Engineering, Machine Design .
    Krus, Petter
    Linköping University, The Institute of Technology. Linköping University, Department of Mechanical Engineering, Machine Design.
    A multi-objective optimization approach to aircraft preliminary design2004In: SAE Transactions Journal of Aerospace, p. 454-460Article in journal (Refereed)
  • 85.
    Ölvander, Johan
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Mechanical Engineering, Machine Design.
    Krus, Petter
    Linköping University, The Institute of Technology. Linköping University, Department of Mechanical Engineering, Machine Design.
    Optimizing the Optimization - A Method for Comparison of Optimization Algorithms2006In: AIAA Multidisciplinary Design Optimization Specialists Conference,2006, Newport, RI; USA: AIAA , 2006Conference paper (Refereed)
  • 86.
    Ölvander, Johan
    et al.
    Linköping University, Department of Management and Engineering, Machine Design . Linköping University, The Institute of Technology.
    Lundén, Björn
    Linköping University, Department of Management and Engineering, Machine Design . Linköping University, The Institute of Technology.
    Gavel , Hampus
    Saab Aerosystems.
    A computerized optimization framework for the morphological matrix applied to aircraft conceptual design2009In: Computer-Aided Design, ISSN 0010-4485, E-ISSN 1879-2685, Vol. 41, no 3, p. 187-196Article in journal (Refereed)
    Abstract [en]

    This paper presents a formal mathematical framework for the use of the morphological matrix in a computerized conceptual design framework. Within the presented framework, the matrix is quantified so that each solution principle is associated with a set of characteristics such as weight, cost, performance, etc. Selection of individual solutions is modeled with decision variables and an optimization problem is formulated. The applications are the conceptual design of subsystems for an Unmanned Aerial Vehicle and an aircraft fuel transfer system. Both the system models and the mathematical framework are implemented in MS Excel.

  • 87.
    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.

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