Necmettin Kaya

Machining fixture locating and clamping position optimization using genetic algorithms

Deformation of the workpiece may cause dimensional problems in machining. Supports and locators are used in order to reduce the error caused by elastic deformation of the workpiece. The optimization of support, locator and clamp locations is a critical problem to minimize the geometric error in workpiece machining. In this paper, the application of genetic algorithms (GAs) to the fixture layout optimization is presented to handle fixture layout optimization problem. A genetic algorithm based approach is developed to optimise fixture layout through integrating a finite element code running in batch mode to compute the objective function values for each generation. Case studies are given to illustrate the application of proposed approach. Chromosome library approach is used to decrease the total solution time. Developed GA keeps track of previosly analyzed designs, therefore the number of function evaulations are decreased about 93%. The results of this approach show that the fixture layout optimization problems are multi-modal problems. Optimized designs do not have any apparent similarities although they provide very similar performances.

Neuro-Genetic Design Optimization Framework to Support the Integrated Robust Design Optimization Process in CE

This article describes an integrated and optimized product design framework to support the design optimization applications in concurrent engineering (CE). The significant consideration is given to show the effectiveness of hybrid approaches and how they can be used to improve the performance of integrated design optimization applications. The proposed approach is based on two-stages which are (1) the use of neural networks (NNs) and genetic algorithm (GA) with feature technology for integrated design activities and (2) the use of Taguchi’s method and GA for design parameters optimization. The first stage resulted in better integrated design solutions in terms of computational complexity and later resulted in a solution, which leads to better and more robust parameter values for multi-objective shape design optimization. The effectiveness and validity of the proposed approach are evaluated with examples.

OPTIMAL DESIGN OF VEHICLE COMPONENTS USING TOPOLOGY DESIGN AND OPTIMISATION

An important problem in automotive industry is how to achieve better design concepts by considering structure performance and manufacturing cost in the early stages of product development. The topology design and optimisation provide an initial design concept for downstream applications, which leads to achieving better design by using computer-aided techniques. In this research, engine mount bracket design is presented to illustrate the application of topology optimisation approach for optimal design of vehicle components under dynamic loading conditions. The objective of the proposed research is to create an initial design concept, which has optimal structural layout. The effectiveness and verification of proposed approach are demonstrated with experimental results.

Hybrid approach for genetic algorithm and Taguchi's method based design optimization in the automotive industry

Although genetic algorithm and multi-objective optimization techniques are widely used to solve problems in the design and manufacturing area, further improvements are required to develop more efficient techniques regarding multi-objective optimization problems. The main goal of the present research is to further develop and strengthen the genetic algorithm based multi-objective optimization approach to generate real-world design solutions in the automotive industry. In this research, a new hybrid approach based on Taguchis method and a genetic algorithm is presented to achieve better Pareto-optimal set solutions for multi-objective design optimization problems. In addition, fatigue damage and life are also considered to evaluate the results of the design optimization process. The validity and efficiency of the proposed approach are evaluated and illustrated with test problems taken from the literature. It is then applied to a vehicle component taken from the automotive industry.

Optimal design of an automotive diaphragm spring with high fatigue resistance

In this paper, shape optimisation of an automobile clutch diaphragm spring is performed using a genetic algorithm. In order to have high fatigue resistance, optimum window profile is determined and concentrated stress at the window region is decreased. A genetic algorithm based approach is developed to optimise the diaphragm spring window profile which has concentrated stress, through integrating a finite element code running in batch mode to compute the objective function values for each generation. Finally, a hill climbing local search algorithm is employed to tune the window profile parameters.

Multi-objective crashworthiness design optimisation of thin-walled tubes

Thin-walled structural members contribute significantly to the ability of an automobile body to absorb energy during frontal impact. The objective of this paper is to improve the energy absorption performance of crash tubes that are placed behind the bumper in automotive vehicles using shape and size optimisation. The best cross section is determined initially, and then dynamic axial crushing simulation is carried out on thin-walled octagonal tube, which has crush initiators. In order to maximise the absorbed energy, shape and size, optimisation techniques are applied using a response surface approximation technique. The design of experiment method is employed to construct the response surfaces. An explicit finite element code, LS-DYNA, was used to implement the parallel computations.

Optimisation of vehicle engine mount system using simulation-based design approach

The engine mount systems have a significant effect with respect to reducing the vehicle development time and cost regarding NVH characteristics and shortcomings not solved yet. There is still a need to enhance the performance of engine mount systems for vehicle ride comfort. This research presents a simulation-based approach to design optimised engine mount components to isolate the road- and engine-induced vibrations without the need for physical prototypes. Experimental tests are performed to define hyperelastic and viscoelastic models for non-linear finite element simulations of rubber components. After the correlation between the results of simulations and the product tests, a virtual engine mount model is presented to design optimum engine mount systems with the desired static and dynamic characteristics. The stiffness curves of different shapes of designs are investigated, and the best curve is chosen as an optimum design solution using the design of experiments approach.

Hyperelastic modelling and shape optimisation of vehicle rubber bushings

The main functions of a rubber bushing are to join the rigid elements in the vehicles and isolate vibration and noise. Owing to the increasing interest of multi-body simulations of vehicles, it is important to develop validated models to calculate the static stiffness. Mechanical behaviour of rubber products depends on many parameters, therefore their modelling is quite complex. In this study, a hyperelastic finite element model of rubber bushing was developed, analysed and compared with test results. Optimum design parameters of bushing model were determined by shape optimisation using differential evolution algorithm.

Hot stamping applications in the automotive industry: coupled numerical simulation and FE-based die design

Hot stamping is an alternative production method for forming of ultra-high strength sheet metals. It consists of heating the sheet metal and directly transfers to the die through the forming and cooling steps. Today, there is an increasing trend to use the hot stamping process to manufacture vehicle parts owing to body structure regarding vehicle safety and emission requirements. The aim of this study is to present a numerical simulation approach, which is FE-based die design for hot stamping with a thermo-mechanical-metallurgical coupled model. The results and validity of this approach are illustrated through an industrial application for an automotive part. The results are also evaluated by considering hot stamping applications research in literature, and 2D and 3D results show a good agreement with results known from literature.

Effect and Optimization of Resistance Spot Welding Parameters on the Strength of Welded Hot-Stamped Parts

Abstract In this study, the effects of three control parameters for the resistance spot welding of hot-stamped parts were studied. These control parameters are the welding force, welding time, and welding current. Al-Si coated 22MnB5 (USIBOR 1500P) sheets with thicknesses of 1.7 mm and 2 mm were used for the experiments. The Taguchi L9 orthogonal array was used in the experiments. Evaluation of the experiments was based on the shear strengths of the welded specimens. The higher is better equation was selected to analyze the results. The relative importance of the spot welding parameters and their optimal combinations were determined using ANOVA. Additionally, an optimization of the welding parameters to maximize the weld tensile shear was conducted using the differential evolution algorithm, as well as the optimal parameters were determined.