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Bahman Ahmadi

Academic rank: Assistant Professor
ORCID:
Education: PhD.
ScopusId: 12357
Faculty: Faculty of Engineering
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Research

Title
Multi-objective reliability-based optimal synthesis of path generating four-bar mechanisms: A cooperative game theoretic approach
Type
JournalPaper
Keywords
Mechanism synthesis, optimization, reliability-based design, cooperative game
Year
2021
Journal PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF ME
DOI
Researchers Bahman Ahmadi ، Behzad Ahmadi ، Saeed Nezamivand Chegini ، Leili Safari

Abstract

In this study, a novel approach based on synergy of cooperative game theory, reliability-based design optimization (RBDO) and Monte Carlo simulation (MCS) is proposed to address the reliability-based multi-objective optimal synthesis of path generating four-bar mechanisms, taking into account the influence of dimensional uncertainty on the reliability of mechanism. Tracking error (TE), deviation of transmission angle from 90° (TA) and probability of failure of Grashof constraint are defined as three performance criteria whose minimization enhance the precision, quality of motion and reliability of mechanism, respectively. To do so, three objective functions are considered, namely, precision (fTE), quality of motion (fTA) and reliability (fG); each objective function is assigned to a player. To conduct the optimization procedure, a game model is proposed, in which the cooperative game scenario is employed by defining a Nash bargaining function to model the interaction between players. In this way, the three-objective optimum design of mechanism is cast into a single-objective optimization problem. The comparisons of the obtained results using the method of this research with those reported in the literature shows a significant improvement in reliability of mechanism, whilst both precision and quality of motion in deterministic design is maintained. Particularly, the tracking error and the deviation of transmission angle from 90° of the synthesized mechanism is 0.0006 and 666.36 respectively, whilst the reliability is guaranteed since no violation of Grashof constraint occurs in the presence of 10% parameter uncertainty.