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Andersson (Ölvander), Johan
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Publications (10 of 86) Show all publications
Wiberg, A., Persson, J. & Andersson (Ölvander), J. (2019). Design for additive manufacturing – a review of available design methods and software.. Rapid prototyping journal, 25(6), 1080-1094
Open this publication in new window or tab >>Design for additive manufacturing – a review of available design methods and software.
2019 (English)In: Rapid prototyping journal, ISSN 1355-2546, E-ISSN 1758-7670, Vol. 25, no 6, p. 15p. 1080-1094Article, review/survey (Refereed) Published
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. [ABSTRACT FROM AUTHOR]

Publisher
p. 15
Keywords
Additive manufacturing, Design automation, Design for additive manufacturing, Design optimization, Knowledge-based engineering
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:liu:diva-160357 (URN)10.1108/RPJ-10-2018-0262 (DOI)000482449200011 ()
Note

Funding agencies: European Union [738002]

Available from: 2019-09-19 Created: 2019-09-19 Last updated: 2019-09-20
Honarpardaz, M., Andersson (Ölvander), J. & Tarkian, M. (2019). Fast finger design automation for industrial robots. Robotics and Autonomous Systems, 113, 120-131
Open this publication in new window or tab >>Fast finger design automation for industrial robots
2019 (English)In: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 113, p. 120-131Article in journal (Refereed) Published
Abstract [en]

Finger design automation is highly demanded from robot industries to fulfill the requirements of the agile market. Nevertheless, literature lacks a promising approach to automate the design process of reliable fingers for industrial robots. Hence, this work proposes the generic optimized finger design (GOFD) method which automates the design process of single- and multi-function finger grippers. The proposed method includes an optimization algorithm to minimize the design process time. The method is utilized to generate fingers for several groups of objects. Results show that the GOFD method outperforms existing methods and is able to reduce the design time by an average of 16,600 s. While the proposed method substantially reduces the design process time of fingers, the quality of grasps is comparable to the traditional exhaustive search method. The grasp quality of GOFD deviates only 0.47% from the absolute best grasp known from the exhaustive search method in average. The designed fingers are lastly manufactured and experimentally verified.

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
Design automation, Fingers design, Multi-function fingers, Industrial grippers, Optimization, Robotics
National Category
Design Robotics
Identifiers
urn:nbn:se:liu:diva-153950 (URN)10.1016/j.robot.2018.12.011 (DOI)000459358000010 ()2-s2.0-85060074455 (Scopus ID)
Note

Funding agencies: European Communitys Framework Programme Horizon 2020 [644938 - SARAFun]

Available from: 2019-01-21 Created: 2019-01-21 Last updated: 2019-03-29Bibliographically approved
Papageorgiou, A. & Ölvander, J. (2018). A Data Management and Visualization Tool for Integrating Optimization Results in Product Development. In: Ekströmer, Philip; Schütte, Simon and Ölvander, Johan (Ed.), DS 91: Proceedings of NordDesign 2018, Linköping, Sweden, 14th - 17th August 2018: DESIGN IN THE ERA OF DIGITALIZATION. Paper presented at NordDesign 2018, Linköping, Sweden, 14th - 17th August 2018.
Open this publication in new window or tab >>A Data Management and Visualization Tool for Integrating Optimization Results in Product Development
2018 (English)In: DS 91: Proceedings of NordDesign 2018, Linköping, Sweden, 14th - 17th August 2018: DESIGN IN THE ERA OF DIGITALIZATION / [ed] Ekströmer, Philip; Schütte, Simon and Ölvander, Johan, 2018Conference paper, Published paper (Other academic)
Abstract [en]

This paper presents a data management and visualization tool that was developed in parallel with a Multidisciplinary Design Optimization (MDO) framework in order to enable a more effective use of the obtained results within the Product Development Process (PDP). To this date, the main problem is that the majority of MDO case studies conclude by suggesting a small number of optimal configurations, which do not really hold any meaningful value for the decision makers since they represent only a narrow area of the design space. In this light, the proposed tool aims to provide designers with new possibilities in respect to post-processing of large data sets, and subsequently, to allow the non-technical teams to be engaged and benefit from the use of MDO in the company practices. As an example, an Unmanned Aerial Vehicle (UAV) configurator developed by using the Graphical User Interface (GUI) of MATLAB is herein presented, and it is shown that a tool for handling the results can be the logical next step towards integrating MDO in the manufacturing industry. Overall, this work aims to demonstrate the benefits of the present visualization and management tool as a complementary addition to an existing optimization framework, and also to determine if this approach can be the right strategy towards improving the MDO method for an eventual use in the PDP of complex pro-ducts like UAVs.

Series
NordDESIGN
Keywords
Big Data, Digital Design
National Category
Aerospace Engineering
Identifiers
urn:nbn:se:liu:diva-155050 (URN)978-91-7685-185-2 (ISBN)
Conference
NordDesign 2018, Linköping, Sweden, 14th - 17th August 2018
Available from: 2019-03-11 Created: 2019-03-11 Last updated: 2019-03-29Bibliographically approved
Wiberg, A., Persson, J. & Ölvander, J. (2018). AN OPTIMIZATION FRAMEWORK FOR ADDITIVE MANUFACTURING GIVEN TOPOLOGY OPTIMIZATION RESULTS. In: Tools and Methods of Competitive Engineering: Implementation, application and utilization of smart systems. Paper presented at Twelfth International Symposium on Tools and Methods of Competitive Engineering (TMCE 2018), Las Palmas de Gran Canaria, Spain, 7-11 May 2018.
Open this publication in new window or tab >>AN OPTIMIZATION FRAMEWORK FOR ADDITIVE MANUFACTURING GIVEN TOPOLOGY OPTIMIZATION RESULTS
2018 (English)In: Tools and Methods of Competitive Engineering: Implementation, application and utilization of smart systems, 2018Conference paper, Published 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.

Keywords
Additive Manufacturing, Design for Additive Manufacturing, Topology Optimization, Design Optimization, Multidisciplinary Design Op
National Category
Other Mechanical Engineering
Identifiers
urn:nbn:se:liu:diva-150367 (URN)
Conference
Twelfth International Symposium on Tools and Methods of Competitive Engineering (TMCE 2018), Las Palmas de Gran Canaria, Spain, 7-11 May 2018
Available from: 2018-08-20 Created: 2018-08-20 Last updated: 2018-09-18
Papageorgiou, A., Tarkian, M., Amadori, K. & Andersson (Ölvander), J. (2018). Multidisciplinary Optimization of Unmanned Aircraft Considering Radar Signature, Sensors, and Trajectory Constraints. Journal of Aircraft, 55(4), 1629-1640
Open this publication in new window or tab >>Multidisciplinary Optimization of Unmanned Aircraft Considering Radar Signature, Sensors, and Trajectory Constraints
2018 (English)In: Journal of Aircraft, ISSN 0021-8669, E-ISSN 1533-3868, Vol. 55, no 4, p. 1629-1640Article in journal (Refereed) Published
Abstract [en]

This paper presents a multidisciplinary design optimization framework applied to the development of unmanned aerial vehicles with a focus on radar signature and sensor performance requirements while simultaneously considering the flight trajectory. The primary emphasis herein is on the integration and development of analysis models for the calculation of the radar cross section and sensor detection probability, whereas traditional aeronautical disciplines such as aerodynamics and mission simulation are also taken into account in order to ensure a flyable concept. Furthermore, this work explores the effect of implementing trajectory constraints as a supplementary input to the multidisciplinary design optimization process and presents a method that enables the optimization of the aircraft under a three-dimensional flight scenario. To cope with the additional computational cost of the high-fidelity radar cross section and sensor calculations, the use of metamodels is also investigated and an efficient development methodology that can provide high-accuracy approximations for this particular problem is proposed. Overall, the operation and performance of the framework are evaluated against five surveillance scenarios, and the obtained results show that the implementation of trajectory constraints in the optimization has the potential to yield better designs by 12–25% when compared to the more “traditional” problem formulations.

Place, publisher, year, edition, pages
American Institute of Aeronautics and Astronautics, 2018
Keywords
UAV, MDO, RCS, Trajectory, Sensors
National Category
Aerospace Engineering
Identifiers
urn:nbn:se:liu:diva-150980 (URN)10.2514/1.C034314 (DOI)000449304100025 ()2-s2.0-85050865062 (Scopus ID)
Funder
VINNOVA, 2013-03758
Note

Funding agencies: Innovative Multidisciplinary Product Optimization (IMPOz) project of Swedens innovation agency VINNOVA [2013-03758]

Available from: 2018-09-07 Created: 2018-09-07 Last updated: 2018-11-22Bibliographically approved
Papageorgiou, A., Amadori, K., Jouannet, C. & Ölvander, J. (2018). Multidisciplinary Optimization of Unmanned Aircraft in a System of Systems Context. In: : . Paper presented at 31th Congress of the International Council of the Aeronautical Sciences (ICAS) 2018 - Belo Horizonte, Brazil, September 9-14, 2018.
Open this publication in new window or tab >>Multidisciplinary Optimization of Unmanned Aircraft in a System of Systems Context
2018 (English)Conference paper, Published paper (Other academic)
Abstract [en]

This paper explores the use of Multidisciplinary Design Optimization (MDO) in the development of Unmanned Aerial Vehicles (UAVs) when the requirements include a collaboration in a System of Systems (SoS) environment. In this work, the framework considers models that can capture the mission, stealth, and surveillance performance of each aircraft, while at the same time, a dedicated simulation module assesses the total cooperation effect on a given operational scenario. The resulting mixed continuous and integer variable problem is decomposed with a multi-level architecture, and in particular, it is treated as a fleet allocation problem that includes a nested optimization routine for sizing a “yet-to-be-designed” aircraft. Overall, the models and the framework are evaluated through a series of optimization runs, and the obtained Pareto front is compared with the results from a traditional aircraft mission planning method in order to illustrate the benefits of this SoS approach in the design of UAVs.

Keywords
MDO, UAV, SoS
National Category
Aerospace Engineering
Identifiers
urn:nbn:se:liu:diva-155047 (URN)978-3-932182-88-4 (ISBN)
Conference
31th Congress of the International Council of the Aeronautical Sciences (ICAS) 2018 - Belo Horizonte, Brazil, September 9-14, 2018
Available from: 2019-03-11 Created: 2019-03-11 Last updated: 2019-03-22Bibliographically approved
Gopinath, V., Johansen, K. & Andersson (Ölvander), J. (2018). Risk Assessment for Collaborative Operation: A Case Study on Hand-Guided Industrial Robots. In: Valentina Svalova (Ed.), Risk Assessment: . InTech
Open this publication in new window or tab >>Risk Assessment for Collaborative Operation: A Case Study on Hand-Guided Industrial Robots
2018 (English)In: Risk Assessment / [ed] Valentina Svalova, InTech, 2018Chapter in book (Refereed)
Abstract [en]

Risk assessment is a systematic and iterative process, which involves risk analysis, where probable hazards are identified, and then corresponding risks are evaluated along with solutions to mitigate the effect of these risks. In this article, the outcome of a risk assessment process will be detailed, where a large industrial robot is used as an intelligent and flexible lifting tool that can aid operators in assembly tasks. The realization of a collaborative assembly station has several benefits, such as increased productivity and improved ergonomic work environment. The article will detail the design of the layout of a collaborative assembly workstation, which takes into account the safety and productivity concerns of automotive assembly plants. The hazards associated with hand-guided collaborative operations will also be presented.

Place, publisher, year, edition, pages
InTech, 2018
Keywords
Hand-guided robots, industrial system safety, collaborative operations, human-robot collaboration, risk assessment, hazards
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:liu:diva-145504 (URN)10.5772/intechopen.68673 (DOI)9789535137986 (ISBN)9789535137993 (ISBN)
Available from: 2018-03-02 Created: 2018-03-02 Last updated: 2018-03-09Bibliographically approved
Sharifimajd, B., Ölvander, J. & Stålhand, J. (2017). Identification of the mechanical parameters for the human uterus in vivo using intrauterine pressure measurements. International Journal for Numerical Methods in Biomedical Engineering, 33(1), 1-11
Open this publication in new window or tab >>Identification of the mechanical parameters for the human uterus in vivo using intrauterine pressure measurements
2017 (English)In: 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) Published
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.

Place, publisher, year, edition, pages
John Wiley & Sons, 2017
Keywords
human uterine smooth muscle mechanics, intrauterine pressure, parameter identification, response surface methodology
National Category
Applied Mechanics Mechanical Engineering
Identifiers
urn:nbn:se:liu:diva-121014 (URN)10.1002/cnm.2778 (DOI)000393964900001 ()26915913 (PubMedID)2-s2.0-84962638845 (Scopus ID)
Note

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

Available from: 2015-09-02 Created: 2015-09-02 Last updated: 2018-01-03Bibliographically approved
Eek, M., Karlén, J. & Ölvander, J. (2015). A Framework for Early and Approximate Uncertainty Quantification of Large System Simulation Models. In: Proceedings of the 56th Conference on Simulation and Modelling (SIMS 56), October, 7-9, 2015, Linköping University, Sweden: . Paper presented at The 56th Conference on Simulation and Modelling (SIMS 56) 7-9 October 2015 (pp. 91-104). Linköping: Linköping University Electronic Press
Open this publication in new window or tab >>A Framework for Early and Approximate Uncertainty Quantification of Large System Simulation Models
2015 (English)In: Proceedings of the 56th Conference on Simulation and Modelling (SIMS 56), October, 7-9, 2015, Linköping University, Sweden, Linköping: Linköping University Electronic Press, 2015, p. 91-104Conference paper, Published paper (Refereed)
Abstract [en]

Uncertainty Quantification (UQ) is vital to ensure credibility in simulation results and to justify model-based design decisions – especially in early development phases when system level measurement data for traditional model validation purposes are scarce. Central UQ challenges in industrial applications are computational cost and availability of information and resources for uncertainty characterization. In an attempt to meet these challenges, this paper proposes a framework for early and approximate UQ intended for large simulation models of dynamical systems. A Modelica simulation model of an aircraft environmental control system including a liquid cooling circuit is used to evaluate the industrial applicability of the proposed framework.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2015
Series
Linköping Electronic Conference Proceedings, ISSN 1650-3686, E-ISSN 1650-3740 ; 119
Keywords
Uncertainty quantification; aleatory uncertainty; epistemic uncertainty; model validation; aircraft system simulation models; Modelica
National Category
Aerospace Engineering
Identifiers
urn:nbn:se:liu:diva-122480 (URN)10.3384/ecp1511991 (DOI)9789176859001 (ISBN)
Conference
The 56th Conference on Simulation and Modelling (SIMS 56) 7-9 October 2015
Funder
VINNOVA, NFFP6 2013-01211
Available from: 2015-11-04 Created: 2015-11-04 Last updated: 2018-01-25Bibliographically approved
Persson, J., Feng, X., Wappling, D. & Ölvander, J. (2015). A Framework for Multidisciplinary Optimization ofa Balancing Mechanism for an Industrial Robot. Journal of Robotics, 1-8, Article ID 389769.
Open this publication in new window or tab >>A Framework for Multidisciplinary Optimization ofa Balancing Mechanism for an Industrial Robot
2015 (English)In: Journal of Robotics, ISSN 1687-9600, E-ISSN 1687-9619, p. 1-8, article id 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
Keywords
Industrial Robots, Optimization, Multi-Disciplinary, Optimization
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:liu:diva-115938 (URN)10.1155/2015/389769 (DOI)000361964900001 ()
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
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