Metaheuristic optimization algorithms have gained relevance and have effectively been investigated for solving complex real design problems in diverse fields of science and engineering. In this paper, a recent meta-heuristic approach inspired by human social concepts, namely the queuing search algorithm (QSA), is implemented for the first time to optimize the main parameters of the spur gear, in particular, to minimize the weight of a single-stage spur gear. The effectiveness of the algorithm introduced is examined in two steps. First, the algorithm used is compared with descriptions in previous studies and indicates that the final results obtained by QSA lead to a reduction in gear weight by 7.5 %. Furthermore, the outcomes obtained are compared with those for the other five algorithms. The results reveal that the QSA outperforms the techniques with which it is compared such as the sine-cosine optimization algorithm, the ant lion optimization algorithm, the interior search algorithm, the teaching-learning-based algorithm, and the jaya algorithm in terms of robustness, success rate, and convergence capability.
In this study, two recent algorithms, the whale optimization algorithm and moth-flame optimization, are used to optimize spur gear design. The objective function is the minimization of the total weight of the spur gear pair. Moreover, the optimization problem is subjected to constraints on the main kinematic and geometric conditions as well as to the resistance of the material of the gear system. The comparison between moth-flame optimization (MFO), the whale optimization algorithm (WOA), and previous studies indicate that the final results obtained from both algorithms lead to a reduction in gear weight by 1.05 %. MFO and the WOA are compared with four additional swarm algorithms. The experimental results indicate that the algorithms introduced here, in particular MFO, outperform the four other methods when compared in terms of solution quality, robustness, and high success rate.
The aim of this work is to synthesize a cam mechanism with translating roller follower based on optimization approaches and reliability analysis. The study consists of two parts. At first, this study performs preliminary deterministic optimization to find the optimum size of a cam system and to ensure its high operating performance. For this, an objective function is defined and that takes into account the three major design parameters typically influence the design of this type of mechanism: the base radius of the cam, the radius of the roller and the eccentricity. Also, constraints on performance and resistance indicators such as the acceptable pressure angles, size radius of curvature of directories curves, the efficiency of the transmission and the specific contact pressure between the cam and follower are taken into account in this work. The second part is devoted to a reliability-mechanism study whose system failure probability is estimated by two complementary methods: the approximation methods FORM / SORM and Monte Carlo simulation using the Phimeca reliability engineer Software. Moreover, inverse FORM was used to provide an elasticity factors evaluation in order to carry out possibilities of the cam mechanism design and reliability improvement. The study has shown that the reliability is greatly improved.
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