Multi-criteria fuzzy decision support for conceptual evaluation in design of mechatronic systems: a quadrotor design case study

Designing mechatronic systems is known to be a very complex and tedious process due to the high number of system components, their multi-physical aspects, the couplings between the different domains involved in the product, and the interacting design objectives. This inherent complexity calls for th...

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Bibliographic Details
Published in:Research in engineering design Vol. 29; no. 3; pp. 329 - 349
Main Authors: Mohebbi, Abolfazl, Achiche, Sofiane, Baron, Luc
Format: Journal Article
Language:English
Published: London Springer London 01.07.2018
Springer Nature B.V
Subjects:
Agglomeration
Artificial neural networks
CAE) and Design
Complexity
Computer simulation
Computer-Aided Engineering (CAD
Couplings
Criteria
Decision making
Design
Design engineering
Domains
Engineering
Engineering Design
Fuzzy logic
Fuzzy systems
Integrals
Multiple criterion
Neural networks
Objectives
Original Paper
Fuzzy logic
Multi-criteria design
Mechatronic systems
Quadrotor system
Decision support
ISSN:0934-9839, 1435-6066
Online Access:Get full text
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Summary:Designing mechatronic systems is known to be a very complex and tedious process due to the high number of system components, their multi-physical aspects, the couplings between the different domains involved in the product, and the interacting design objectives. This inherent complexity calls for the crucial need of a systematic and multi-objective design thinking methodology to replace the often-used sequential design approach that tends to deal with the different domains and their corresponding design objectives separately leading to functional but not necessarily optimal designs. Thus, a new approach based on a multi-criteria profile for mechatronic systems is presented in this paper for the conceptual design stage. Additionally, to facilitate fitting the intuitive requirements for decision-making in the presence of interacting criteria, three different methods are proposed and compared using a case study of designing a vision-guided quadrotor drone system. These methods benefit from three different aggregation techniques such as Choquet integral, Sugeno integral and fuzzy-based neural network. To validate the decision yielded by the results of global concept score for each aggregation methods, a computer simulation of a visual servoing system on all design alternatives for quadrotor drone has been performed. It is shown that although the Sugeno fuzzy can be a useful aggregation function for decisions under uncertainty, but the approaches using Choquet fuzzy and fuzzy integral-based neural network seem to be more precise and reliable in a multi-criteria design problem where interaction between the objectives cannot be overlooked.
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ISSN:0934-9839
1435-6066
DOI:10.1007/s00163-018-0287-6