Optimization of Process Parameters on Surface Hardness and Energy Consumption in Milling of 7050 Aluminum Alloy using Enhanced NSGA-II

2021 ◽  
Author(s):  
Yang Yang ◽  
Chen Su ◽  
Hongsen Wang ◽  
Yuan Wang ◽  
Leshi Shu
Keyword(s):  
Aluminum Alloy ◽  
Energy Consumption ◽  
Surface Hardness ◽  
Population Diversity ◽  
Parameters Optimization ◽  
Numerical Control ◽  
Adaptive Mutation ◽  
Nsga Ii ◽  
Milling Parameters ◽  
7050 Aluminum Alloy

Abstract Aluminum alloy has high strength and light weight. It is widely used for aircraft fuselage, propellers and other parts which work under high load conditions. High-quality parts made of aluminum alloy processed by computerized numerical control (CNC) machine often have the characteristics of high cost in their processing. In order to achieve high surface quality and control processing costs, this article takes the workpiece surface hardness and machining energy consumption as targets. Intelligent optimization algorithm is used to find the optimal combination of milling parameters to obtain ideal targets. CNC milling parameter optimization is a multi-parameter, multi-objective, multi-constraint, discrete nonlinear optimization problem which is difficult to solve. For this challenge, an improved NSGA-II is presented, named enhanced population diversity NSGA-II (EPD-NSGA-II). EPD-NSGA-II is improved with the normal distribution crossover, adaptive mutation operator of differential evolution, crowding calculation method considering variance and modified elite retention strategy to achieve enhanced population diversity. 12 test functions are chosen for experimentation to verify the performance of the EPD-NSGA-II. The values of three evaluation indicators show that the proposed approach has good distribution and convergence performance. Finally, the approach is applied in the milling parameters optimization of 7050 aluminum alloy to get the optimal solutions. Results indicate that the EPD-NSGA-II is effective in optimizing the problem of milling parameters.

Research on Finite Element Simulation and Parameters Optimization of Milling 7050-T7451 Aluminum Alloy Thin-walled Parts

2020 ◽  
Vol 14 ◽  
Author(s):  
Song Yang ◽  
Tie Yin ◽  
Feiyue Wang
Keyword(s):  
Aluminum Alloy ◽  
Complex Structure ◽  
Parameters Optimization ◽  
Thin Wall ◽  
Machining Parameters ◽  
Milling Parameters ◽  
Machining Deformation ◽  
Milling Temperature ◽  
Thin Walled ◽  
Milling Forces

Background: Thin-walled parts of aluminum alloy are easy to occur machining deformation duo to the characteristics of thin wall, low rigidity, and complex structure. Objective: To reduce and control the machining deformation, it is necessary to select reasonable machining parameters. Method: The influence of milling parameters on the milling forces, milling temperature, and machining deformation was analyzed through the established model based on ABAQUS. Then, the corresponding empirical formula was obtained by MATLAB, and parameters optimization was carried out as well. Besides, a lot of patents on machining thin-walled parts were studied. Results: The results shown that the prediction error of milling forces is about 15%, and 20% of milling temperature. In this case, the optimized milling parameters are as follows: ap=1 mm, ae=0.1 mm, n=12 000 r/min, and f=400 mm/min. It is of great significance to reduce the machining deformation and improve the machining quality of thin-walled parts.

Research on the Properties of Milling and the Process Parameters Optimization for Aluminum-Alloy Thin-Walled Parts

2010 ◽  
Vol 44-47 ◽  
pp. 2842-2846
Author(s):  
Xiao Hui Jiang ◽  
Bei Zhi Li ◽  
Jian Guo Yang ◽  
He Long Wu
Keyword(s):  
Aluminum Alloy ◽  
Process Parameters ◽  
Low Cost ◽  
Parameters Optimization ◽  
Milling Parameters ◽  
Milling Simulation ◽  
Optimization Of Process Parameters ◽  
Thin Walled ◽  
Parts Manufacturing

In this paper, with the milling processing of aluminum-alloy thin-walled parts as the research object, using software AdvantEdge, a milling simulation model is developed to study milling parameters affect on the cutting force, heat and catenation. It is found that by adjusting the ratio of milling parameters, the effects of cutting forces and heat can turn to the favorable direction of workpiece. In addition, we combine numerical simulation with experiments to explore the law of optimization of process parameters. It is discovered that the method of improving the milling speed and reducing the cutting depth properly can ensure the milling efficiency and the quality of the workpiece, providing a scientific insight for achieving high-quality, low-cost and efficient thin-walled parts manufacturing.

scholarly journals Assessing a Multi-Objective Genetic Algorithm with a Simulated Environment for Energy-Saving of Air Conditioning Systems with User Preferences

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 344
Author(s):  
Alejandro Humberto García Ruiz ◽  
Salvador Ibarra Martínez ◽  
José Antonio Castán Rocha ◽  
Jesús David Terán Villanueva ◽  
Julio Laria Menchaca ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Energy Saving ◽  
User Satisfaction ◽  
Air Conditioning ◽  
State Of The Art ◽  
User Preferences ◽  
The State ◽  
Nsga Ii ◽  
Air Conditioning System

Electricity is one of the most important resources for the growth and sustainability of the population. This paper assesses the energy consumption and user satisfaction of a simulated air conditioning system controlled with two different optimization algorithms. The algorithms are a genetic algorithm (GA), implemented from the state of the art, and a non-dominated sorting genetic algorithm II (NSGA II) proposed in this paper; these algorithms control an air conditioning system considering user preferences. It is worth noting that we made several modifications to the objective function’s definition to make it more robust. The energy-saving optimization is essential to reduce CO2 emissions and economic costs; on the other hand, it is desirable for the user to feel comfortable, yet it will entail a higher energy consumption. Thus, we integrate user preferences with energy-saving on a single weighted function and a Pareto bi-objective problem to increase user satisfaction and decrease electrical energy consumption. To assess the experimentation, we constructed a simulator by training a backpropagation neural network with real data from a laboratory’s air conditioning system. According to the results, we conclude that NSGA II provides better results than the state of the art (GA) regarding user preferences and energy-saving.

scholarly journals Optimization of injection molding process for car fender in consideration of energy efficiency and product quality

2014 ◽  
Vol 1 (4) ◽  
pp. 256-265 ◽  
Author(s):  
Hong Seok Park ◽  
Trung Thanh Nguyen
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Injection Molding ◽  
Product Quality ◽  
Process Parameters ◽  
Optimization Problems ◽  
Computational Cost ◽  
Injection Molding Process ◽  
Molding Process ◽  
Nsga Ii

Abstract Energy efficiency is an essential consideration in sustainable manufacturing. This study presents the car fender-based injection molding process optimization that aims to resolve the trade-off between energy consumption and product quality at the same time in which process parameters are optimized variables. The process is specially optimized by applying response surface methodology and using nondominated sorting genetic algorithm II (NSGA II) in order to resolve multi-object optimization problems. To reduce computational cost and time in the problem-solving procedure, the combination of CAE-integration tools is employed. Based on the Pareto diagram, an appropriate solution is derived out to obtain optimal parameters. The optimization results show that the proposed approach can help effectively engineers in identifying optimal process parameters and achieving competitive advantages of energy consumption and product quality. In addition, the engineering analysis that can be employed to conduct holistic optimization of the injection molding process in order to increase energy efficiency and product quality was also mentioned in this paper.

Micromechanical behavior study of forged 7050 aluminum alloy by microindentation

2012 ◽  
Vol 37 ◽  
pp. 491-499 ◽  
Author(s):  
Jiang Li ◽  
Fuguo Li ◽  
Fengmei Xue ◽  
Jun Cai ◽  
Bo Chen
Keyword(s):  
Aluminum Alloy ◽  
Behavior Study ◽  
7050 Aluminum Alloy
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