Optimization of flexible fixture layout to improve form quality using parametric finite element model and mixed discrete-integer genetic algorithm

Dimensional and form accuracy of the workpiece can be improved by effective fixture layout design which shows minimum deformation of the workpiece during machining. Flexible fixtures are inevitable in industries owing to high product variety and shortened production time. Hence, an integrated approach is presented to select the optimum position of locating and clamping elements in a flexible fixture that provide good form accuracy. In this approach, a Parametric Finite Element Model (PFEM) is developed using the information about the workpiece, fixture plan and machining condition. PFEM is used to predict the elastic deformation of the workpiece for the fixture layouts generated using a discrete Genetic Algorithm (GA) with mixed integer-discrete variables. The objective is to minimize the maximum deformation of the workpiece by optimizing fixture layouts. The stability of the workpiece and fixture system is ensured by implementing non-negative reaction force constraints in GA. The proposed approach is applied for a prismatic workpiece to carry out pocket milling operation. The significance of this work is to express the flexibility and computational effectiveness of PFEM to accommodate variation in the workpiece, machining condition and fixture plan while designing flexible fixtures. Further, it highlights a significant reduction in search space due to the use of discrete GA and stability constraint as it takes less objective function calculations. An experimental analysis is performed to study the effectiveness of the proposed approach. Therefore, the proposed approach provides a viable solution to the optimization problem in flexible fixtures.

Variation propagation modeling in multistage machining processes considering form errors and N-2-1 fixture layouts

Variation propagation modeling of multistage machining processes enables variation reduction by making an accurate prediction on the quality of a part. Part quality prediction through variation propagation models, such as stream of variation and Jacobian-Torsor models, often focus on a 3-2-1 fixture layout and do not consider form errors. This paper derives a mathematical model based on dual quaternion for part quality prediction given parts with form errors and fixtures with N-2-1 (N>3) layout. The method uses techniques of Skin Model Shapes and dual quaternions for a virtual assembling of a part on a fixture, as well as conducting machining and measurement. To validate the method, a part with form errors produced in a two-stationed machining process with a 12-2-1 fixture layout was considered. The prediction made following the proposed method was within 0.4% of the prediction made using a CAD/CAM simulation when form errors were not considered. These results validate the method when form errors are neglected and partially validated when considered.

Optimal Design of Fixture Layout for Compliant Part With Application in Ship Curved Panel Assembly

In a ship assembly process, a large number of compliant parts are involved. The ratio of the part thickness to the length or the width is typically 0.001–0.012. Fixture design is a critical task in the ship assembly process due to its impact on the deformation and dimensional variation of the compliant parts. In current practice, fixtures are typically uniformly distributed under the part to be assembled, which is non-optimal, and large dimensional gaps may occur during assembly. This paper proposed a methodology for the optimal design of the fixture layout in the ship assembly process by systematically integrating direct stiffness method and simulated annealing algorithm, which aims to minimize dimensional gaps along the assembly interface to further improve the quality and efficiency of seam welding. The case study shows that the proposed method significantly reduced the dimensional gaps of the compliant curved panel parts in a ship assembly process.

Optimization of Modular Fixture Layout by Minimizing Work-piece Deformation

The authors have requested that this preprint be withdrawn due to author disagreement.

Optimization of Modular Fixture Layout by Minimizing Work-piece Deformation

Machining fixtures are utilized to locate and restrain a workpiece during different manufacturing processes. The workpiece must be properly located and clamped in order to have it to be manufactured according to the prescribed dimensions and tolerance. The real motive of fixture design is to maximize locating accuracy and workpiece firmness while minimizing deformations. The purpose of this research work is to conduct a multi-objective optimization in order to minimize workpiece deflections due to clamping forces and optimized fixture layout by taking into consideration the boundary conditions and loads applied during a machining process. The locators are employed in a 3-2-1 fixture configuration. Then the empirical relations are used to calculate the machining forces and moments generated during drilling and milling processes and after that the workpiece is loaded to model those cutting forces. ANSYS parametric design language (APDL) code which made use of sub-approximation method is utilized to automatically optimize locator and clamp positions. Afterwards the clamping forces are being optimized using balancing force-moment method. Lastly, the maximum deformation of the workpiece against the optimum clamping forces is found by harmonic analysis.

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

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.

Optimal design of fixture layouts for compliant sheet metal assemblies

A preeminent factor in the geometrical quality of a compliant sheet metal assembly is the fixture layout that is utilized to perform the assembly procedure. Despite the presence of a great number of studies about the optimization of assembly fixture layouts, there is not a comprehensive algorithm to optimize all design parameters of fixture layouts for compliant sheet metal assemblies. These parameters are the location and type of hole and slot in each part, the slot orientation, and the number and location of additional clamps. This paper presents a novel optimization method that optimizes all these parameters simultaneously to maximize the geometrical quality of the assemblies. To attain this goal, compliant variation simulations of the assemblies are utilized along with evolutionary optimization algorithms. The assembly springback and contacts between parts are considered in the simulations. After determining the optimal design parameters, the optimal positions of locators are fine-tuned in another stage of optimization. Besides, a top-down design procedure is proposed for applying this method to multi-station compliant assemblies. The presented method is applied to two industrial sample cases from the automotive industry. The results evidence a significant improvement of geometrical quality by utilizing the determined fixture layout from the presented method compared with the original fixture layouts of the sample cases.

Multi-objective optimization of auto-body fixture layout based on an ant colony algorithm

Fixtures are extensively used in many industries such as the car industry, to locate and constrain the sheet part during the assembly stage. Fixture layout affects on deformation of sheet parts. Therefore, fixture layout optimization is crucial to the accuracy and quality of products. In addition, the number of clamps that uses in the fixture is another important factor that must be considered in fixture design. This article presents a novel fixture layout optimization method by combining multi-objective ant colony algorithm (M-ACO) and the finite element method. The proposed method optimizes the fixture layout and the number of clamps simultaneously as a multi-objective problem. An approximation of Pareto frontier is acquired by the proposed method. The fixture layout for the side reinforcement of a car is optimized using the proposed method. The results show that the proposed approach performs effectively to optimize the auto-body fixture layout.