Johan Ölvander
Linköping University
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Publication
Featured researches published by Johan Ölvander.
Advanced Engineering Informatics | 2012
Kristian Amadori; Mehdi Tarkian; Johan Ölvander; Petter Krus
This paper explores novel methodologies for enabling Multidisciplinary Design Optimization (MDO) of complex engineering products. To realize MDO, Knowledge Based Engineering (KBE) is adopted with the aim of achieving design reuse and automation. The aim of the ongoing research at Linkoping University is to shift from manual modeling of disposable geometries to Computer Aided Design (CAD) automation by introducing generic high level geometry templates. Instead of repeatedly modeling similar instances of objects, engineers should be able to create more general models that can represent entire classes of objects. The proposed methodology enables utilization of commercial design tools, hence taking industrial feasibility into consideration. The concept of High Level CAD templates (HLCt) will be proposed and discussed as the building blocks of flexible and robust CAD models, which in turn enables high fidelity geometry in the MDO loop. Furthermore, quantification of the terms flexibility and robustness are presented, providing a means to measure the quality of the geometry models. Finally, application examples are presented in which the outlined framework is evaluated. The applications have been chosen from three ongoing research projects aimed at automating the design of transport aircraft, industrial robots, and micro air vehicles.
Computer-aided Design | 2009
Johan Ölvander; Björn Lundén; Hampus Gavel
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.
IEEE Transactions on Robotics | 2009
Marcus Pettersson; Johan Ölvander
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.
Journal of Engineering Design | 2005
Johan Ölvander
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.
Journal of Mechanical Design | 2012
Mehdi Tarkian; Johan A. Persson; Johan Ölvander; Xiaolong Feng
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 t ...
design automation conference | 2011
Mehdi Tarkian; Johan A. Persson; Johan Ölvander; Xiaolong Feng
This paper presents a multidisciplinary design optimization framework for modular industrial robots. An automated design framework, containing physics based high fidelity models for dynamic simulat ...
international symposium on industrial electronics | 2007
Marcus Pettersson; Johan Ölvander; Hans Andersson
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.
Concurrent Engineering | 2015
Edris Safavi; Mehdi Tarkian; Hampus Gavel; Johan Ölvander
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.
Engineering Optimization | 2013
Petter Krus; Johan Ölvander
Design optimization is becoming an increasingly important tool for design, often using simulation as part of the evaluation of the objective function. A measure of the efficiency of an optimization algorithm is of great importance when comparing methods. The main contribution of this article is the introduction of a singular performance criterion, the entropy rate index based on Shannons information theory, taking both reliability and rate of convergence into account. It can also be used to characterize the difficulty of different optimization problems. Such a performance criterion can also be used for optimization of the optimization algorithms itself. In this article the Complex-RF optimization method is described and its performance evaluated and optimized using the established performance criterion. Finally, in order to be able to predict the resources needed for optimization an objective function temperament factor is defined that indicates the degree of difficulty of the objective function.
design automation conference | 2007
Xiaolong Feng; S. Sander Tavalley; Johan Ölvander
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 ...