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Engine-bracket drilling fixture layout optimization for minimizing the workpiece deformation

机译:发动机支架钻孔夹具布局优化,以使工件变形最小化

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摘要

Purpose Fixture layout design is concerned with immobilization of the workpiece (engine mount bracket) during machining such that the workpiece elastic deformation is reduced. The fixture holds the workpiece through the positioning of fixturing elements that causes the workpiece elastic deformation, in turn, leads to the form and dimensional errors and increased machining cost. The fixture layout has the major impact on the machining accuracy and is the function of the fixturing position. The position of the fixturing elements, key aspects, needed to be optimized to reduce the workpiece elastic deformation. The purpose of this study is to evaluate the optimized fixture layout for the machining of the engine mount bracket. Design Methodology Approach In this research work, using the finite element method (FEM), a model is developed in the MATLAB for the fixture-workpiece system so that the workpiece elastic deformation is determined. The artificial neural network (ANN) is used to develop an empirical model. The results of deformation obtained for different fixture layouts from FEM are used to train the ANN and finally the empirical model is developed. The model capable of predicting the deformation is embedded to the evolutionary optimization techniques, capable of finding local and global optima, to optimize the fixture layouts and to find the robust one. Findings For efficient optimization of the fixture layout parameters to obtain the least possible deformation, ant colony algorithm (ACA) and artificial bee colony algorithm (ABCA) are used and the results of deformation obtained from both the optimization techniques are compared for the best results. Research Limitations Implications A MATLAB-based FEM technique is able to provide solutions when the repeated modeling and simulations required i.e. modeling of fixture layouts (500 layouts) for every variation in the parameters requires individual modeling and simulation for the output requirement in any FEM-based software's (ANSYS, ABACUS). This difficulty is reduced in this research. So that the MATLAB-based FEM modeling, simulation and optimization is carried out to determine the solutions for the optimized fixture layout to reach least deformation. Practical Implications Many a time the practicability of the machining/mechanical operations are difficult to perform costly and time-consuming when more number of experimentations are required. To sort out the difficulties the computer-based automated solution techniques are highly required. Such kind of research over this study is presented for the readers. Originality Value A MATLAB-based FEM modeling and simulation technique is used to obtain the fixture layout optimization. ANN-based empirical model is developed for the fixture layout deformation that creates a hypothesis for the fixture layout system. ACA and ABCA are used for optimizing the fixture layout parameters and are compared for the best algorithm suited for the fixture layout system.
机译:目的夹具布局设计涉及在加工过程中的工件(发动机安装支架)的固定,使得工件弹性变形减小。夹具通过固定元件的定位保持工件,该固定元件导致工件弹性变形又导致形式和尺寸误差和增加的加工成本。夹具布局对加工精度具有主要影响,并且是固定位置的功能。固定元件的位置,需要优化以减少工件弹性变形所需的关键方面。本研究的目的是评估用于加工发动机支架的优化夹具布局。设计方法方法在本研究中的工作中,使用有限元方法(FEM),在Matlab中开发模型,用于夹具工件系统,从而确定工件弹性变形。人工神经网络(ANN)用于开发经验模型。从FEM的不同夹具布局获得的变形结果用于训练ANN,最后开发了经验模型。能够预测变形的模型嵌入到能够找到本地和全局最优的进化优化技术,以优化夹具布局并找到坚固的优化。使用夹具布局参数的有效优化的发现,使用蚁群算法(ACA)和人造群菌落算法(ABCA)以及从两种优化技术获得的变形结果以获得最佳结果。研究限制影响,基于MATLAB的有限元技术能够在所需的重复建模和模拟时提供解决方案,即针对参数中的每个变化的固定建模(500布局)建模需要各个建模和仿真,以便在任何FEM的任何FEM中的输出要求软件的(Ansys,Abacus)。这项研究减少了这种困难。因此,进行了基于MATLAB的有限元模拟,模拟和优化,以确定优化的夹具布局以达到最小变形的解决方案。许多时候,当需要更多数量的实验时,许多时间难以执行加工/机械操作的实用性。要整理困难,因此非常需要基于计算机的自动化解决方案技术。对读者提供了这项研究的这种研究。最初值A基于MATLAB的FEM建模和仿真技术用于获得夹具布局优化。基于ANN的实证模型是为夹具布局变形开发的,为夹具布局系统产生假设。 ACA和ABCA用于优化固定布局参数,并与适用于夹具布局系统的最佳算法进行比较。

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