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Persson, Johan
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Publications (10 of 14) Show all publications
Wiberg, A., Persson, J. & 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.

Place, publisher, year, edition, pages
Emerald Group Publishing Limited, 2019. 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 ()2-s2.0-85070356872 (Scopus ID)
Note

Funding agencies: European Union [738002]

Available from: 2019-09-19 Created: 2019-09-19 Last updated: 2019-10-14Bibliographically 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: 2019-10-14
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
Blomkvist, J., Persson, J. & Åberg, J. (2015). Communication through Boundary Objects in Distributed Agile Teams. In: : . Paper presented at CHI '15 CHI Conference on Human Factors in Computing Systems (pp. 1875-1884). New York, NY, USA: Association for Computing Machinery (ACM), 33
Open this publication in new window or tab >>Communication through Boundary Objects in Distributed Agile Teams
2015 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Personal communication between User-Centered Design (UCD) specialists and developers is important for communicating user needs and design solutions in agile development. In distributed projects where opportunities for personal communication are limited, the design documentation is an important surrogate. This study has investigated the perceived effectiveness of boundary objects in a distributed agile team, and their role in communicating target user needs. Six in-depth interviews with UCD specialists showed that the boundary objects rarely communicate underlying needs of the users but rather focus on interaction with the system that is being developed. The used boundary objects also do not work as stand-alone deliverables; they need to be explained and elaborated. Making the boundary objects comprehensive enough to be stand-alone is seen as too time consuming and not worth the effort. For agile projects with distributed teams, this creates hand-over and follow-up problems.

Place, publisher, year, edition, pages
New York, NY, USA: Association for Computing Machinery (ACM), 2015
National Category
Human Computer Interaction
Identifiers
urn:nbn:se:liu:diva-118676 (URN)10.1145/2702123.2702366 (DOI)000412395501108 ()978-1-4503-3145-6 (ISBN)
Conference
CHI '15 CHI Conference on Human Factors in Computing Systems
Available from: 2015-06-03 Created: 2015-06-03 Last updated: 2018-07-17Bibliographically approved
Persson, J. (2015). Efficient Optimization of Complex Products: A Simulation and Surrogate Model Based Approach. (Doctoral dissertation). Linköping: Linköping University Electronic Press
Open this publication in new window or tab >>Efficient Optimization of Complex Products: A Simulation and Surrogate Model Based Approach
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

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

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

These areas include

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

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

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2015. p. 88
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1655
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:liu:diva-115939 (URN)10.3384/diss.diva-115939 (DOI)978-91-7519-083-9 (ISBN)
Public defence
2015-04-24, ACAS, A-huset, Campus Valla, Linköping, 10:15 (English)
Opponent
Supervisors
Funder
EU, FP7, Seventh Framework Programme, Crescendo no. 234244VINNOVA, IMPOz no. 2013-03758
Available from: 2015-03-24 Created: 2015-03-24 Last updated: 2015-04-17Bibliographically approved
Persson, J. & Ölvander, J. (2015). Optimization of the Complex-RFM Optimization Algorithm. Optimization and Engineering, 16(1), 27-48
Open this publication in new window or tab >>Optimization of the Complex-RFM Optimization Algorithm
2015 (English)In: Optimization and Engineering, ISSN 1389-4420, E-ISSN 1573-2924, Vol. 16, no 1, p. 27-48Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Springer-Verlag New York, 2015
Keywords
Optimization, Surrogate models, Meta-optimization
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-84849 (URN)10.1007/s11081-014-9247-9 (DOI)000351842300002 ()
Note

This article status has been changed from Manuscript to Article in Journal.

Available from: 2012-10-24 Created: 2012-10-24 Last updated: 2017-12-07Bibliographically approved
Persson, J., Feng, X., Wappling, D. & Ölvander, J. (2014). Multi-disciplinary and multi-objective optimization of a hydro-pneumatic balancing cylinder for an industrial robot. In: ASME 2014 12th Biennial Conference on Engineering Systems Design and Analysis, ESDA 2014: . Paper presented at ASME 2014 12th Biennial Conference on Engineering Systems Design and Analysis, ESDA 2014. Web Portal ASME (American Society of Mechanical Engineers), 3
Open this publication in new window or tab >>Multi-disciplinary and multi-objective optimization of a hydro-pneumatic balancing cylinder for an industrial robot
2014 (English)In: ASME 2014 12th Biennial Conference on Engineering Systems Design and Analysis, ESDA 2014, Web Portal ASME (American Society of Mechanical Engineers) , 2014, Vol. 3Conference paper, Published paper (Refereed)
Abstract [en]

This article presents an optimization framework that is used to optimize a hydro-pneumatic balancing cylinder for industrial robots. A balancing cylinder is a device that is used to balance the gravitational torque of one of the main axes of a high-loaded serial industrial robot. The design of components for an industrial robot is multi-disciplinary, since disciplines such as multibody dynamics, drive train design and robot control are needed. The design process is also multi-objective since the functionality of the balancing cylinder should be optimal, while its size and cost should be minimal. The article therefore also contains a discussion about multi-disciplinary and multi-objective optimization of complex products.

Place, publisher, year, edition, pages
Web Portal ASME (American Society of Mechanical Engineers), 2014
Series
ASME 2014 12th Biennial Conference on Engineering Systems Design and Analysis, ESDA 2014
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:liu:diva-116726 (URN)10.1115/ESDA2014-20463 (DOI)000361407000086 ()2-s2.0-84916897900 (Scopus ID)9780791845851 (ISBN)
Conference
ASME 2014 12th Biennial Conference on Engineering Systems Design and Analysis, ESDA 2014
Available from: 2015-04-09 Created: 2015-04-02 Last updated: 2015-10-13
Persson, J. & Ölvander, J. (2013). Comparison of Different Uses of Metamodels for Robust Design Optimization. Paper presented at 51st AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition 7 - 10 January 2013, Texas, USA.
Open this publication in new window or tab >>Comparison of Different Uses of Metamodels for Robust Design Optimization
2013 (English)Conference paper, Published paper (Other academic)
Abstract [en]

This paper compares different approaches for using kriging metamodels for robust design optimization, with the aim of improving the knowledge of the performance of the approaches. A popular approach is to first fit a metamodel to the original model and then perform the robust design optimization on the metamodel. However, it is also possible to create metamodels during the optimization. Additionally, the metamodel need not necessarily reanimate the original model; it may also model the mean value, variance or the actual objective function. The comparisons are made with two analytical functions and a dynamic simulation model of an aircraft system as an engineering application. In the comparisons, it is seen that creating a global metamodel before the optimization begins slightly outperforms the other approaches that involve metamodels.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-84848 (URN)
Conference
51st AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition 7 - 10 January 2013, Texas, USA
Available from: 2012-10-24 Created: 2012-10-24 Last updated: 2015-03-24Bibliographically approved
Persson, J. (2012). Design and Optimization under Uncertainties: A Simulation and Surrogate Model Based Approach. (Licentiate dissertation). Linköping: Linköping University Electronic Press
Open this publication in new window or tab >>Design and Optimization under Uncertainties: A Simulation and Surrogate Model Based Approach
2012 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis deals with development of complex products via modeling and simulation, and especially the use of surrogate models to decrease the computational efforts when probabilistic optimizations are performed. Many methods that can be used to perform probabilistic optimizations exist and this thesis strives to present and demonstrate the capabilities of a few of them. Hopefully, this information can be helpful for someone who wants to choose a method.

Knowledge about several different topics is required to perform a probabilistic optimization. First, it is necessary to incorporate the probabilistic behavior into the analysis by estimating how the uncertainties and variations in the model and its parameters are affecting the performance of the system. The focus in this thesis is on sampling based methods to estimate these probabilities. Secondly, an optimization algorithm should be chosen so that the computer can search for and present an optimal solution automatically.

The probabilistic optimization process can be computationally demanding since numerous simulations of the model are performed each time the value of the objective function is estimated. It is therefore desirable to speed up the process by incorporating computationally effective surrogate models. This is especially important if the simulated model is computationally demanding on its own, e.g. a finite element model with many nodes.

Each of these topics is presented in its own chapter of this thesis. A few  methods are presented and their performances demonstrated for each topic.

Surrogate models can also be used to improve the performances of optimization algorithms when the desire is to optimize computationally expensive objective functions. With this in mind, efforts have been made to improve the Complex-RF optimization algorithm. A modified algorithm is presented in this thesis and the main difference is that it creates and utilizes surrogate models iteratively during the optimization process. The modified algorithm is compared with Complex-RF and is demonstrated to be superior for computationally expensive models.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2012. p. 81
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1556
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-84850 (URN)978-91-7519-753-1 (ISBN)
Presentation
2012-11-02, Mass, A-huset, Campus Valla, Linköpings universitet, Linköping, 10:15 (Swedish)
Opponent
Supervisors
Funder
EU, FP7, Seventh Framework Programme, 234344
Available from: 2012-10-24 Created: 2012-10-24 Last updated: 2012-10-24Bibliographically approved
Tarkian, M., Persson, J., Ölvander, j. & Feng, X. (2012). Multidisciplinary Design Optimization of Modular Industrial Robots by Utilizing High Level CAD templates. Journal of mechanical design (1990), 134(12)
Open this publication in new window or tab >>Multidisciplinary Design Optimization of Modular Industrial Robots by Utilizing High Level CAD templates
2012 (English)In: Journal of mechanical design (1990), ISSN 1050-0472, E-ISSN 1528-9001, Vol. 134, no 12Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
American Society of Mechanic, 2012
National Category
Other Mechanical Engineering
Identifiers
urn:nbn:se:liu:diva-81878 (URN)10.1115/1.4007697 (DOI)
Note

On the day of the defence day the status of this article was: Manuscript

Available from: 2012-09-24 Created: 2012-09-24 Last updated: 2017-12-07Bibliographically approved
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