From the past few decades, parallel grippers are used successfully in the automation industries for performing various pick and place jobs due to their simple design, reliable nature and its economic feasibility. So, the purpose of this paperis to design a suitable gripper with appropriate design parameters for better performance in the robotic production systems.,In this paper, an enhanced multi-objective ant lion algorithm is introduced to find the optimal geometric and design variables of a parallel gripper. The considered robotic gripper systems are evaluated by considering three objective functions while satisfying eight constraint equations. The beta distribution function is introduced for generating the initial random number at the initialization phase of the proposed algorithm as a replacement of uniform distribution function. A local search algorithm, namely, achievement scalarizing function with multi-criteria decision-making technique and beta distribution are used to enhance the existing optimizer to evaluate the optimal gripper design problem. In this study, the newly proposed enhanced optimizer to obtain the optimum design condition of the design variables is called enhanced multi-objective ant lion optimizer.,This study aims to obtain optimal design parameters of the parallel gripper with the help of the developed algorithms. The acquired results are investigated with the past research paper conducted in that field for comparison. It is observed that the suggested method to get the best gripper arrangement and variables of the parallel gripper mechanism outperform its counterparts. The effects of the design variables are needed to be studied for a better design approach concerning the objective functions, which is achieved by sensitivity analysis.,The developed gripper is feasible to use in the assembly operation, as well as in other pick and place operations in different industries.,In this study, the problem to find the optimum design parameter (i.e. geometric parameters such as length of the link and parallel gripper joint angles) is addressed as a multi-objective optimization. The obtained results from the execution of the algorithm are evaluated using the performance indicator algorithm and a sensitivity analysis is introduced to validate the effects of the design variables. The obtained optimal parameters are used to develop a gripper prototype, which will be used for the assembly process.

中文翻译：

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使用灵敏度分析方法的增强型多目标蚁狮优化器的并行机器人夹具的优化设计

在过去的几十年里，平行夹具因其简单的设计、可靠的特性和经济可行性而成功地用于自动化行业，用于执行各种取放作业。因此，本文的目的是设计一种具有适当设计参数的合适夹具，以在机器人生产系统中获得更好的性能。在本文中，引入了一种增强的多目标蚁狮算法来寻找最佳几何和设计变量。平行夹持器。通过考虑三个目标函数同时满足八个约束方程来评估所考虑的机器人夹具系统。Beta 分布函数被引入用于在所提出的算法的初始化阶段生成初始随机数作为均匀分布函数的替代。局部搜索算法，即具有多准则决策技术和β分布的成就标量函数被用来增强现有的优化器来评估最佳的抓手设计问题。在本研究中，新提出的用于获得设计变量最佳设计条件的增强型优化器称为增强型多目标蚁狮优化器。本研究旨在借助开发的算法获得平行夹具的最佳设计参数。将获得的结果与过去在该领域进行的研究论文进行比较，以进行比较。据观察，获得最佳夹具布置和平行夹具机构变量的建议方法优于其对应方法。需要研究设计变量的影响，以获得关于目标函数的更好设计方法，这是通过灵敏度分析实现的。开发的夹具可用于组装操作以及其他拾取和放置操作在不同的行业。,在这项研究中，寻找最佳设计参数（即几何参数，如连杆长度和平行夹爪关节角度）的问题作为多目标优化来解决。使用性能指标算法评估算法执行获得的结果，并引入敏感性分析来验证设计变量的效果。获得的最佳参数用于开发夹具原型，该原型将用于装配过程。