Multi-Objective Optimization of Quality in Laser Cutting Based on Response Surface Model

2013 ◽  
Vol 756-759 ◽  
pp. 3712-3716
Author(s):  
Hui Juan Hao ◽  
Mao Li Wang ◽  
Feng Qi Hao
Keyword(s):  
Response Surface ◽  
Laser Cutting ◽  
Removal Rate ◽  
Quality Characteristics ◽  
Surface Model ◽  
Multi Objective Optimization ◽  
Yag Laser ◽  
Multi Objective ◽  
Important Means

Prediction and optimization of quality characteristics is an important means to improve the quality of laser cutting. Kerf width (KW) and material removal rate (MRR) are selected as the quality characteristics in this paper. The fitting response surface models (RSM) of KW and MRR are considered as the optimization objective function in pulsed Nd: YAG laser cutting of alloy steel for multi-objective optimization. An improved Pareto genetic algorithm is used in the optimization, and the significant factors have been found. The predicted results are basically consistent with the experimental. Therefore, the method used in this paper can be used for optimization of KW and MRR in pulse Nd: YAG laser cutting. The study can provide theoretical basis for the prediction and optimization of quality in laser cutting.

Optimization of Laser Cut Quality Characteristics Considering Material Removal Rate Based on Pareto Concept

2014 ◽  
Vol 657 ◽  
pp. 216-220
Author(s):  
Miloš Madić ◽  
Miroslav Radovanović ◽  
Laurenţiu Slătineanu ◽  
Oana Dodun
Keyword(s):  
Mathematical Models ◽  
Material Removal Rate ◽  
Laser Cutting ◽  
Material Removal ◽  
Removal Rate ◽  
Quality Characteristics ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Cut Quality ◽  
Pareto Fronts

Stainless steels are one of the most important engineering materials widely used in the industry. This paper presents multi-objective optimization of CO2 laser cutting of stainless steel considering different cut quality characteristics and material removal rate (MRR). Laser cutting experiment trials were conducted based on Taguchis L27 experimental design by varying the laser power, cutting speed, assist gas pressure and focus position at three levels. Using obtained experimental data, six mathematical models for the prediction of surface roughness, kerf width, kerf taper angle, width of heat affected zone, dross height and MRR were developed using artificial neural network (ANN). The developed mathematical models were taken as objective functions for the multi-objective optimization using genetic algorithm based on Pareto concept. As a result of multi-objective optimization, five 2-D Pareto fronts were generated covering all combinations of cut quality characteristics and MRR. It was observed that the mathematical relationships in the Pareto fronts between MRR and cut quality characteristics are in some cases linear and in another nonlinear.

Finite Element Analysis and Multi-Objective Optimization of the Precision Horizontal Machining Center Bed

2014 ◽  
Vol 889-890 ◽  
pp. 130-134
Author(s):  
Xue Yan Li ◽  
Wen Tie Niu ◽  
Jun Qiang Wang ◽  
Ling Jun Xue
Keyword(s):  
Response Surface ◽  
Response Surface Model ◽  
Least Square ◽  
Surface Model ◽  
Multi Objective Optimization ◽  
Element Analysis ◽  
Maximum Deformation ◽  
Multi Objective ◽  
Machining Center ◽  
Sample Points

In order to improve dynamic and static performance of the precision horizontal machining center, the method of multi-objective optimization based on the response surface model was applied for optimizing design of the bed structure. The design variables were the layout parameters of the rib plates. Sample points were obtained by the Box-Behnken design experiment, and responses of sample points were analyzed by SAMCEF. The maximum deformation of guide rails and the low-order natural frequency were extracted to fit the response surface model by least square method. The layout parameters of the rib plates were optimized through the application of multi-objective genetic algorithms. Then, relationship between the lightening holes and the performance were analyzed to determine the suitable diameter. The results verify the validity of the optimization method, and the paper provides methodological guidance for optimization of machine tool structural parts.

Multi-Objective Optimization of a Bolt-Flange Structure

2011 ◽  
Vol 233-235 ◽  
pp. 2800-2804
Author(s):  
Yuan Dong Liu ◽  
Yi Hui Yin ◽  
Ying Chun Lu
Keyword(s):  
Response Surface ◽  
Design Method ◽  
Equivalent Stress ◽  
Optimization Method ◽  
Surface Model ◽  
Geometrical Parameters ◽  
Multi Objective Optimization ◽  
Surface Design ◽  
Multi Objective ◽  
Maximum Equivalent Stress

The bolt-flange structure is most one of joint mode, and stress and mass are its major performance parameters. The multi-object optimization of a bolt-flange structure can be performed by using Finite element method and optimization method unitedly. The response surface design method was employed to determine the combination of geometrical parameters to be designed of the bolt-flange structure. The stress of the bolt-flange structure which has the different geometrical parameters was numerically simulated and analyzed by using the software ANSYS. The response surface model is obtained. The optimized geometrical parameters of the bolt-flange structure were obtained by using MATLAB multi-objective optimization method. The results showed that the maximum equivalent stress in the optimized bolt-flange structure decreased 13.4% than that in the original one and the mass of the optimized bolt-flange structure was lower 14.3% than that of the original one.

Design and optimization of spin micro-generator's rotating rack used in trajectory correction fuze under high-impact loadings

2018 ◽  
Vol 233 (13) ◽  
pp. 4421-4438
Author(s):  
Jianghai Hui ◽  
Min Gao ◽  
Xinpeng Li
Keyword(s):  
Elastic Modulus ◽  
Response Surface ◽  
Coupling Model ◽  
Response Surface Model ◽  
Surface Model ◽  
Multi Objective Optimization ◽  
Design And Optimization ◽  
Multi Objective ◽  
Trajectory Correction ◽  
Buffer Structure

Buffer structure is a traditional measure to improve the ammunition's performance of withstanding impact loadings during launch process. On that basis, this paper proposes a parametric optimization for the gasket, which is served as buffer structure in spin microgenerator's rotating rack used in trajectory correction fuze to effectively reduce the stress of bearings used in the rack. It is a finite element dynamic simulation based on rack-projectile-barrel coupling to acquire variation of the bearings' stress. A rack-projectile-barrel coupling model is built and the simulation pre-process is described. At first, the parametric analysis for the gasket is conducted. The effect of the gasket's axial thickness and elastic modulus on the bearings' stress is studied, and the results show that singly changing one of the two gasket's parameters cannot effectively reduce the two-ball bearings' stress. Then, based on the two gasket's parameters, the design of experiment method is applied with 25 sample points established. A kind of approximation, response surface model is created and its fitting accuracy is verified. Single-objective and multi-objective optimization are conducted based on the response surface model, respectively. And the multi-objective optimization for the gasket can successfully reduce the two bearings' stress to the value below the bearing material's yield strength. In addition, to check the optimization's effectiveness, an experiment is carried out and the results indicate that the gasket whose axial thickness and elastic modulus have been optimized can effectively improve the rotating rack's performance of withstanding impact loadings.

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