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

• Published in: Engineering computations Vol. 38; no. 5; pp. 1978 - 2002
• Main Authors: T, Ramachandran, S, Surendarnath, R, Dharmalingam
• Format: Journal Article
• Language: English
• Published: Bradford Emerald Publishing Limited 30.06.2021; Emerald Group Publishing Limited
• Subjects: Ant colony optimization; Artificial neural networks; Automation; Boundary conditions; Brackets; CAD; Computer aided design; Computer simulation; Deformation; Design of experiments; Elastic deformation; Finite element method; Fixtures; Geometry; Layouts; Machining; Mathematical models; Matlab; Modelling; Optimization algorithms; Optimization techniques; Parameters; Search algorithms; Swarm intelligence; Variables; Workpieces; Finite element method; ANN; Engine mount bracket; Fixture layout; Workpiece elastic deformation; Optimization
• ISSN: 0264-4401; 1758-7077
• DOI: 10.1108/EC-04-2020-0194

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.