1 Copyright © 2014 by ASME Proceedings of the ASME 12th Biennial Conference on Engineering Systems Design and Analysis ESDA2014 June 25-27, 2014 - Copenhagen, Denmark ESDA2014-20414 MECHATRONIC MULTICRITERIA PROFILE (MMP) FOR CONCEPTUAL DESIGN OF A ROBOTIC VISUAL SERVOING SYSTEM Abolfazl Mohebbi Dept. of Mechanical Engineering École Polytechnique Montréal, Canada abolfazl.mohebbi@polymtl.ca Sofiane Achiche Dept. of Mechanical Engineering École Polytechnique Montréal, Canada sofiane.achiche@polymtl.ca Luc Baron Dept. of Mechanical Engineering École Polytechnique Montréal, Canada luc.baron@polymtl.ca Niels Henrik Mortensen Dept. of Mechanical Engineering Technical University of Denmark nhmo@mek.dtu.dk ABSTRACT Mechatronic systems are a combination of cooperative mechanical, electronics and control components. The high number of their components, their multi-physical aspect, the couplings between the different domains involved and the interacting design objectives makes the design task very tedious ad complex. Due to this inherent complexity, a concurrent systematic and multi-objective design thinking methodology is crucial to replace the often used sequential design approach that tends to deal with the different domains separately. In this research we present a new multi-criteria profile for mechatronic system performance evaluation in conceptual design stage. The newly introduced Mechatronic Multi-criteria Profile (MMP) includes various quantitative members such as intelligence, reliability, complexity, flexibility and cost. A nonlinear fuzzy integral called 2-additive Choquet Integral will be used for the aggregation of criteria and fitting the intuitive requirements for decision-making in the presence of interacting criteria. Finally, the effectiveness of the proposed method will be validated via a case study of designing a robotic visual servoing system. 1. INTRODUCTION Mechatronic systems are of increased importance in engineering and their relevance goes hand in hand with the increasing complexity of the tasks they perform. Design of a wide variety of products such as transportation systems, aircrafts, robots, construction machines or even home appliances are now considered within the area of mechatronic systems. Mechatronic systems are combinations of cooperative mechanical, electronics and control components. The high number of their components, their multi-physical aspect and the couplings between the different domains involved makes the design task very tedious ad complex [1, 2] . Due to the inherent complexity cited above and the dynamic coupling between subsystems of a mechatronic systems, a systematic and multi- objective design thinking methodology is crucial to replace the often used sequential design approach that tends to deal with the different domains (mechanical, electrical, software, fluid, thermal, etc.) separately. The results are products that would eventually form a special integration and a functional interaction in components, modules, products and systems. Zhang et al. [3] proposed an integrated approach for mechatronic design of a programmable closed-loop mechanical system. They used an objective function to reduce the shaking force and moment and consequently to facilitate the design of the control system. As an improvement to this work, Li et al. [4] developed a concurrent design framework known as design for control (DFC). Their idea was founded on the basis that, although controller parameters could be changed after the machine is built, they should be designed simultaneously with the structural parameters. Same as [3], to facilitate controller design, the reduction of the shaking force/moment of the actuators, was the only objective they considered for their method. Although an effective concurrent approach was introduced in their work, improving the system performance using changeability of the controller parameters has been overlooked. Yet, other important criteria in the evaluation of design have not been considered in their research. Seo et al. [5] developed an automated mechatronic design methodology using the integration of genetic programming and bond graph modelling, where only the structural part of the mechatronic system is considered and the controller part, which is always present in a mechatronic system, is missing. Furthermore, the performance of the design is measured only by physical parameters. A number of problems and limitations are encountered when design in early stages which requires selection of components and choosing between alternatives for software and