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The search for an efficient design optimization methodology for haptic devices
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Machine Design (Div.).ORCID iD: 0000-0002-6528-1371
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.).ORCID iD: 0000-0001-6692-2794
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.).
(English)In: Engineering with Computers, ISSN 0177-0667, E-ISSN 1435-5663Article in journal (Refereed) Submitted
Abstract [en]

Design optimization of haptic devices must manage multiple objectives,complex models, and time-consuming simulations. This paper proposes amethodology to eciently and eectively optimize the design of a high-performing6-degree-of-freedom (DOF) haptic device. The proposed methodology adapts ametamodel selection method called Predictive Estimation of Model Fidelity (PEMF)method, and integrates it with metamodel-based design optimization (MBDO)process in a multi-tool framework. A 6-DOF TAU haptic device, with two designobjectives, the global isotropy index (GII) and the dexterous workspace volumeindex (VI), is used to exemplify and verify the methodology. Two additional studiesare made to nd the most suitable sample size for metamodel training, and tostudy the eects of metamodel combinations on the solution accuracy. The generalityof the ndings is veried with MBDO of a completely dierent 6-DOF hapticdevice based on a Stewart Platform. The proposed metamodel-based methodologyreduces the computational time about 27 times as compared to using the fullmodel. For the specied design optimization problem, 300 sample points are ableto provide accurate enough metamodels and system solutions. The combination ofthe best-t metamodel for each design objective, Kriging (KR) for GII and RadialBasis Functions (RBF) for VI, can provide suciently accurate solutions whichlikely are applicable for all types of 6-DOF haptic devices.

Keyword [en]
design optimization, multi-objective, metamodel, predictive estimation of model fidelity
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-217325OAI: oai:DiVA.org:kth-217325DiVA: diva2:1155509
Note

QC 20171108

Available from: 2017-11-08 Created: 2017-11-08 Last updated: 2017-11-08Bibliographically approved
In thesis
1. A methodology for situated and effective design of haptic devices
Open this publication in new window or tab >>A methodology for situated and effective design of haptic devices
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The realism of virtual surgery through a surgical simulator depends largely on the precision and reliability of the haptic device. The quality of perception depends on the design of the haptic device, which presents a complex design task due to the multi-criteria and conflicting character of the functional and performance requirements. In the model-based evaluation of the performance criteria of a haptic device, the required computational resources increase with the complexity of the device structure as well as with the increased level of detail that is created in the detail design phases. Due to uncertain requirements and a significant knowledge gap, the design task is fuzzy and more complex in the early design phases.

The goal of this thesis is to propose a situated, i.e., flexible, scalable and efficient, methodology for multi-objective and multi-disciplinary design optimization of high-performing 6-DOF haptic devices.

The main contributions of this thesis are:

1. A model-based and simulation-driven engineering design methodology and a flexible pilot framework are proposed for design optimization of high-performing haptic devices. The multi-disciplinary design optimization method was utilized to balance the conflicting criteria/requirements of a multi-domain design case and to solve the design optimization problems concurrently.

2. A multi-tool framework is proposed. The framework integrates metamodel-based design optimization with complementary engineering tools from different software vendors, which was shown to significantly reduce the total computationally effort.

3. The metamodeling methods and sampling sizes for specific performance indices found from case studies were shown to be applicable and usable for several kinds of 6-degrees-of-freedom haptic devices.

4. The multi-tool framework and the assisting methodology were further developed to enable computationally efficient and situated design multi-objective optimization of high-performing haptic devices. The design-of-experiment (DOE) and metamodeling techniques are integrated with the optimization process in the framework as an option to solve the design optimization case with a process that depends on the present system complexity.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2017. 66 p.
Series
TRITA-MMK, ISSN 1400-1179 ; 2017:13
Keyword
Design optimization, haptic devices, metamodel, multi-criteria, situatedness
National Category
Mechanical Engineering
Research subject
Machine Design
Identifiers
urn:nbn:se:kth:diva-217327 (URN)978-91-7729-573-0 (ISBN)
Public defence
2017-11-29, Gladan, Brinellvägen 85, Stockholm, 10:00 (English)
Supervisors
Note

QC 20171108

Available from: 2017-11-08 Created: 2017-11-08 Last updated: 2017-11-08Bibliographically approved

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Sun, XuanAndersson, Kjell

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