Iterative Fixture Layout and Clamping Force Optimization Using the Genetic Algorithm

Machining fixture layout optimization using the genetic algorithm

Fixture Layout Design (FLD) determines the specific position of locators and clamps to orient and holds the workpiece with respect to a machine tool. The FLD approaches that use Finite Element Analysis (FEA) have been widely used in previous works and have become computationally expensive and specific to a particular problem. Further, the FLD and clamping force optimization were often performed separately by ignoring their interdependence. In the present work, the locators' contact forces are uniformly distributed by suitably varying the fixture layout and clamping force to maximize the part dimensional and form quality. The parametric rigid body model is used to depict the behaviour of the workpiece-fixture system, and it is incorporated with the genetic algorithm to optimize the design variables. A prismatic workpiece with pocket milling operation is considered to validate the proposed methodology. Stability criterion and tool-fixture interference are considered constraints. Subsequently, FEA is used to verify the integrity of the proposed approach. The results infer that the uniform distribution of maximum elastic deformation is achieved due to the uniform distribution of contact forces. The suggested approach is proven effective for designing a milling fixture to manufacture components with high dimensional and form precision.

Fixture layout for machining thin-walled structures plays an important role in fixture performance. This work focuses on the optimization design of machining fixture layout including clamp layout and the layout of support heads. A universal optimization methodology that can automatically generate the optimal machining fixture layout is proposed. The optimization of fixture layout is implemented based on the criteria of minimizing maximum deflection of the thin-walled workpiece while remain relatively small torque caused by the clamping tables. An evolutionary algorithm is employed to solve the fixture layout optimization for the optimal solution. The optimal position of the support heads and the layout of clamping tables obtained from this work vary along with the change of cutting force. To validate the proposed optimization methodology, a fixture layout design for a typical thin-walled structure is optimized as an example. The case study demonstrates the application of the proposed approach in the fixture layout design for thin-walled structures, which is beneficial to design an optimal fixture layout.

Optimisation of machining fixture layout under multi-constraints

Recently, highly porous metal foams have been used to replace the traditional open-flow channels to improve gas transport and distribution in the cells. Deformation of flow plate, gas diffusion layer (GDL), and metal foam may occur during assembling. When the cell size is small, the deformation may not be significant. For large area cells, the deformation may become significant to affect the cell performance. In this study, an assembling device that is capable of applying uniform clamping force is built to facilitate fuel cell assembling and alleviate the deformation. A compressing plate that is the same size of the active area is used to apply uniform clamping force before surrounding bolts are fastened. Therefore, bending of the flow plate and deformation of GDL and metal foam can be minimized. Effects of the clamping force on the microstructures of GDL and metal foam, various resistances, pressure drops, and cell performance are investigated. Distribution of the contact pressure between metal foam and GDL is measured by using pressure sensitive films. Field-emission scanning electron microscope is used to observe the microstructures. Electrochemical impedance spectroscopy analysis is used measure resistances. The fuel cell performance is measured by using a fuel cell test system. For the cell design used in this study, the optimum clamping force is found to be 200 kgf. Using this optimum clamping force, the cell performance can be enhanced by 50%, as compared with that of the cell assembled without using clamping plates. With appropriate clamping force, the compression force distribution across the entire cell area can approach uniform. This enables uniform flow distribution and reduces mass transfer resistance. Good contact between GDL and metal foam also lowers the interface resistance. All these factors contribute to the enhanced cell performance.

The effects of frictional damping on the dynamic response of a beam structure have been investigated. The frictional damping was contributed from the slip mechanisms in a ‘pseudo’ joint, that is a joint that did not take any static load. Using pseudo joints for vibration control has significant advantages over using joints that are designed both to take static load and to introduce frictional damping; because there is almost no restriction on the configuration of the pseudo joint, the undesirable side effects related to the frictional damping such as fretting corrosion of contact surfaces and loss of static stiffness are zero if the frictional damping from a pseudo joint is utilized. An ‘optimum’ clamping force was found which minimized the magnitude of the frequency response function (FRF) of the structure under excitation. A reduction of about 20 dB in the amplitudes of the FRFs was achieved by adjusting the clamping force at the joint. Frictional damping was found to be significant over the measured frequency range of 20-2000 Hz, and it was particularly effective over the range of 20-1000 Hz. The magnitudes of the FRFs of the structure were determined by the ratio of clamping force to excitation force. They were insensitive to the change of clamping force near its optimum value; also the optimum clamping force was not sensitive to small modifications to the structure. Therefore, utilizing frictional damping in pseudo joints is an effective technique for vibration control.

Fixture layout is an essential factor in intelligent manufacturing in the shipbuilding industry, affecting assembly quality and efficiency. Its optimization has become an urgent problem in the assembly process of compliant parts. Traditional fixture layout depends on workers’ experience, which leads to butt clearance along the assembly interface. Thus, this article proposes a butt clearance control-oriented fixture layout optimization (BCCFLO) methodology. First, a method for calculating the part dimensional variation under the influence of fixture layout and fixture locating error is developed. Then, a constrained multi-objective integer nonlinear programming (CMINP) model is innovatively formulated to optimize the fixture layout. Furthermore, the non-dominated sorting genetic algorithm-II based on Latin hypercube sampling is designed to address the CMINP model. The case study illustrates and validates that the fixture layout achieved by the proposed method could significantly control the butt clearance for large compliant part assembly in the shipbuilding industry.

For auto-body, fixture layout is very important to gravity deformation and dimensional variation of sheet metal assemblies. Conventionally, the satisfying fixture layouts can be generated by global optimization algorithms, such as genetic algorithm (GA), particle swarm optimization (PSO) and social radiation algorithm (SRA), etc. However, it is very difficult to generate the global optimalsolution because the combinations of fixture layouts are enormousand the gravity deformation must be calculated by finite element analysis for sheet metal parts. Therefore, this paper proposes a hybrid algorithm of GAOT (genetic algorithm in optimization toolbox in MATLAB) and RBF-NN(Radial basis function - neural network) to generate the global optimal fixture layouts. In this paper, the fixture locators are selected from a much smaller candidate pool based on filtering methods. The objective function is the gravity deformation of all measurement operations. A hybrid algorithm of GAOT and RBF-NN is used to optimize fixture locating scheme based on MATLAB macro commands of 3DCS, whose optimization process is fully automated. A case of bracketis applied to demonstrate the proposed method in this paper. The results show that the proposedhybridalgorithm can generate better optimal solutions thanthe current optimization methods.

This paper describes the effects of the clamping force and the pre-clamping force on the fatigue strength of bolt-connection. The results obtained are as follows:(1) The types of load-deflection diagrams of bolt-connection with the clamping force were classified into cross-type and un-cross-type.(2) And also, theoretical expressions of the optimum clamping force and the pre-clamping force were inducted to the both types of the diagrams.(3) The theoretical values of the optimum clamping force nearly fitted to the experimental values.(4) The experimental values of the fatigue limits on the optimum clamping force for the M 5 bolt of bolt-connection increased about 40% against the conventional value, at mean stress σm = 30 kg/mm2.(5) The effects of the pre-clamping force on the bolt-connection were inducted with the improvements on the compressive residual stress in bolt-connection and the optimum clamping force.

Optimisation of fixture layout is critical to reduce geometric and form error of the workpiece during the machining process. In this paper the optimal placement of fixture elements (locator and clamp locations) under dynamic conditions is investigated using evolutionary techniques. The application of the newly developed particle swarm optimisation (PSO) algorithm and widely used genetic algorithm (GA) is presented to minimise elastic deformation of the workpiece considering its dynamic response. To improve the performances of GA and PSO, an improved GA (IGA) obtained by basic GA (GA) with sharing and adaptive mutation and an improved PSO (IPSO) obtained by basic PSO (PSO) incorporated into adaptive mutation are developed. ANSYS parametric design language (APDL) of finite element analysis is employed to compute the objective function for a given fixture layout. Three layout optimisation cases derived from the high speed slot milling case are used to test the effectiveness of the GA, IGA, PSO and IPSO based approaches. The comparisons of computational results show that IPSO seems superior to GA, IGA and PSO approaches with respect to the trade-off between global optimisation capability and convergence speed for the presented type problems.

Fixture Design Optimisation Considering Production Batch of Compliant Non-Ideal Sheet Metal Parts

Machining fixture locating and clamping position optimization using genetic algorithms

Machining fixtures are used to locate and arrest the workpiece from deformation during machining operation. Fixture layout is the process of placing the locators and clamps in suitable position. The accuracy and quality of finished workpiece is depending on the number of fixturing elements and their positions. In this work, the fixture layout has been optimized by optimizing the number of fixture elements with optimal location. Initially 3-2-1 locating scheme has been followed to minimize the workpiece deformation, then the number of fixture elements are introduced to formthe new fixture plans such as 3-2-2, 3-3-1and 3-3-2. Finally, the optimum numbers of fixturing elements are confirmed. Moment equations has been developed for each fixture elements. Genetic algorithm-based optimization procedure is followed for obtaining optimum fixture layout. The moment equations are given to the GA as input objective function. Finite element solver ANSYS is used for predicting the workpiece deformation for various fixturing layouts.

Machining accuracy of thin-walled parts is easily affected by clamping and cutting deformation due to its poor stiffness. In this paper, synchronous optimization method of clamping force and cutting parameters is presented based on GA and FEM. The optimization objective is to minimize the maximum deformation and to improve the machining efficiency. GA is used to optimize cutting parameters and clamping force, and FEM is used to predict the machining deformation of the thin-walled workpiece. Finally, taking a titanium alloy thin-walled part with irregular shape as an example, the optimal clamping force and cutting parameters at every cutting position are obtained to demonstrate the feasibility of the method.

This paper studies a fixture layout optimization problem for the ship assembly. Current studies focus on the positioning problem, i.e., optimizing the positions of a constant number of fixtures, while less considers the sizing problem, i.e., deciding the number of used fixtures. In most of the cases, it is difficult to assure that the adopted number of fixtures can lead to a layout that satisfies all the engineering requirements. The objective of this paper is to minimize the number of fixtures required while optimizing their positions, ensuring adherence to a set of engineering constraints. These include the maximum allowed nodal displacement and the assembly gap between two parts. We propose an efficient two-step metaheuristic approach. In the first step, fixtures are added iteratively to the parts until a feasible layout is achieved. In the second step, a large neighborhood search is employed to remove fixtures while maintaining the feasibility of the layout. To mitigate the computational cost required by finite element simulation, a Kriging model is proposed to evaluate the neighborhood solutions. Numerical experiments show that the proposed method can efficiently solve the fixture sizing and positioning problem in a case study of ship panel assembly. The efficacy of the Kriging model in accelerating layout optimization has been validated. Furthermore, the efficiency of the proposed method is demonstrated through comparisons with two existing approaches in the literature. Note to Practitioners—This paper was motivated by the problem of holding large compliant parts in the ship assembly process. Sheet metals with a low thickness-to-length ratio are susceptible to deformation during assembly when an inappropriate fixture layout is adopted. Existing approaches for layout design focus on optimizing the positions of the fixtures, while the number of fixtures needs to be determined based on engineering experience. This paper suggests a new approach to determine the minimum number of fixtures required, as well as their positions, to guarantee a set of quality requirements provided by the user. This approach employs the direct stiffness method to evaluate part deformation and an efficient metaheuristic to optimize the layout. During the optimization procedure, we use the Kriging technique to predict the layout’s performance, allowing us to obtain high-quality solutions with lower simulation efforts. We demonstrate that the proposed method can successfully generate a layout that satisfies the quality specifications in a case study of ship panel assembly. In comparison to two existing approaches, the proposed method yields a feasible layout with fewer fixtures, thereby reducing fixture setup time and building costs.