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Robust design of a robot gripper mechanism using new hybrid grasshopper optimization algorithm
Author(s) -
Yildiz Betül Sultan,
Pholdee Nantiwat,
Bureerat Sujin,
Yildiz Ali Riza,
Sait Sadiq M.
Publication year - 2021
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/exsy.12666
Subject(s) - computer science , engineering optimization , robot , mechanism (biology) , clutch , optimization problem , multidisciplinary design optimization , optimization algorithm , mechanism design , mathematical optimization , control engineering , algorithm , artificial intelligence , automotive engineering , engineering , mathematics , epistemology , multidisciplinary approach , sociology , economics , microeconomics , social science , philosophy
Structural design and optimization are important topics for the control and design of industrial robots. The motivation behind this research is to design a robot gripper mechanism. To explore robust design of the robot gripper mechanism, a new optimization approach based on a grasshopper optimization algorithm and Nelder–Mead algorithm is developed for requiring a fast and accurate solution. Additionally, a vehicle side crash design problem, a multi‐clutch disc problem, and a manufacturing optimization problem are solved with the developed method to show the advantages of the new technique (HGOANM). Both engineering comparisons and production problem results in which HGOANM is applied are compared with the latest optimization techniques in the literature. The results of the problems resolved in this article reveal that the developed HGOANM is an essential optimization approach by solving real‐world engineering problems quickly and accurately.