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A novel optimized design of a piezoelectric-driven 4-stage amplified compliant microgripper using a 2-step multi-objective algorithm

Haghshenas Gorgani, H ; Sharif University of Technology | 2022

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  1. Type of Document: Article
  2. DOI: 10.1007/s42452-022-05005-z
  3. Publisher: Springer Nature , 2022
  4. Abstract:
  5. Abstract: Advancements in microscale technologies have prompted a demand for high precision micro-manipulation. Microgrippers are the primary means of conducting micro-scale operations, and they significantly affect the procedure's performance. This paper presents a novel optimized design for compliant microgrippers, intending to enhance functionality and durability. The mainframe of the proposed microgripper is based on a compact flexure-based compliant structure with four stages of movement amplification. Experiments were designed based on the L25 Taguchi orthogonal arrays. The experiments were conducted using the finite element method in Abaqus 6.14 workbench. Range of motion and maximum created mechanical stress are selected as the two fundamental goals of the optimization. A variety of designs are achieved using the proposed algorithm. The use of Analytical Hierarchy Process has led to the presentation of an efficient and well-defined algorithm to perform decisions. The decision process can be performed with regard to specific requirements of various applications. The presented design process of microgrippers has the potential for customized manufacturing for specific applications. Article Highlights: Finding correlations between design parameters and outputs (Amplification factor & Stress), using Taguchi's method in design of experiments (DOE).Optimization of dimensional inputs using a multi-objective genetic algorithm process to achieve an optimal Pareto-front instead of a single design point.Selecting the desirable point on the optimal Pareto-front for specific applications using Analytic Hierarchy Process (AHP) to prevent possible decision-making errors. © 2022, The Author(s)
  6. Keywords:
  7. Compliant mechanism ; Microgripper ; Multi-objective optimization ; Non-dominated sorting genetic algorithm (NSGA-II) ; Abstracting ; Analytic hierarchy process ; Compliant mechanisms ; Decision making ; Design of experiments ; Genetic algorithms ; Grippers ; Mechanisms ; Micro gripper ; Multi-objectives optimization ; Multi-stage amplification ; Multi-stages ; Non dominated sorting genetic algorithm (NSGA II) ; Non-dominated sorting genetic algorithm (NSGA-II) ; Optimisations ; Optimized designs ; Pareto front ; Multiobjective optimization
  8. Source: SN Applied Sciences ; Volume 4, Issue 4 , 2022 ; 25233971 (ISSN)
  9. URL: https://link.springer.com/article/10.1007/s42452-022-05005-z