Study on the Multiple Objective Parameter Optimization Method for NC Turning

2010 ◽  
Vol 102-104 ◽  
pp. 705-709 ◽  
Author(s):  
Zhi Qiang Liu ◽  
Mian Hao Zhang
Keyword(s):  
Material Removal ◽  
Orthogonal Experiment ◽  
Optimization Method ◽  
Taguchi Methods ◽  
Single Precision ◽  
Objective Parameter ◽  
Turning Center ◽  
Set Up ◽  
Tools Wear ◽  
Turning Parameter

Nowadays NC cutting processing has become one of the basic methods of machine manufacture. However, the single precision has failed to meet the demand for the modern manufacture. The surface roughness, tools wear and material removal ratio are used as the objective to research, the orthogonal experiment is built by the Taguchi methods, and the fuzzy analysis is adopted to set up semantic rules between turning parameter and the objects. Then the Taguchi method is used to obtain the optical turning parameter. The QTN200M-500U NC turning center is used to carry out the turning experiment; Results from the experiments could be used as the references for future manufacturing designs.

The Radial Fretting Character Research of the Shaft-Hub of Compress Impeller Based on Virtual Orthogonal Experiment

2014 ◽  
Vol 668-669 ◽  
pp. 289-293
Author(s):  
Xue Long Lu ◽  
Jun Sheng Zhao ◽  
Xin Zhong Huang ◽  
Shuang Yong Wang
Keyword(s):  
Orthogonal Experiment ◽  
Orthogonal Design ◽  
Three Dimensional ◽  
Element Model ◽  
Optimization Method ◽  
Three Dimensional Model ◽  
Interference Fit ◽  
Rotating Speed ◽  
Compressor Impeller ◽  
Set Up

A three-dimensional model of as haft-hub of compressor impeller was set up by Pro/E. Based on the ANSYS; the finite element model was established, using the analysis method of combining submodle and paramesh. The shaft-hub of compressor impeller was simulated by virtual orthogonal design optimization method. Based on the fact that there existed radial fretting in the shaft-hub interference fit joint, researching the influence significance order and law of interference, friction coefficient and rotating speed to the maximum unit frictional work , the average friction work and the optimized parameter were obtained. It turned out that the results of the numerical simulation and orthogonal experiment were accurate and reliable, with the friction and wear effectively reduced, certain guiding references to actual assembly process were got.

Optimization of Process Parameters Based on Multi-Process and Multi-Evaluation Index for Function Ceramics in CMP

2013 ◽  
Vol 797 ◽  
pp. 266-272
Author(s):  
Zi Hua Hu ◽  
Jiao Peng ◽  
Man Ke Gao
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Orthogonal Experiment ◽  
Weight Ratio ◽  
Optimization Method ◽  
Evaluation Index ◽  
Optimization Of Process Parameters

To enhance polishing quality, polishing efficiency and improve the backward state based on single-process way for function ceramics in CMP, a new optimization method of process parameters based on multi-process and multi-evaluation theory is put forward. Firstly, based on experimental data obtained from orthogonal experiment, the optimal combinations of process parameters are got separately in term of surface roughness and material removal rate, which is optimized by Taguchi method in each process. Secondly, combining analysis of evaluation index weight ratio with analysis of variance, the final optimal combination of process parameters is received under the integrated evaluation of surface roughness and material removal rate. Finally, the contrast verification results show that the proposed optimization method is effective.

Study on the Prediction of Drilling Forces on Cortical Bone Based on Finite Element Simulation

2013 ◽  
Vol 589-590 ◽  
pp. 157-162
Author(s):  
Ya Hui Hu ◽  
Qing Yun Zhang ◽  
Xiao Yu Yue
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Feed Rate ◽  
Orthogonal Experiment ◽  
Element Model ◽  
Drilling Speed ◽  
Drilling Force ◽  
Drill Diameter ◽  
Potential Damage ◽  
Set Up

The changes of drilling forces during bone drilling provide a useful index for evaluating the risk of potential damage to the bone. The aim of the work is that an elastic-plastic dynamic finite element model is used to simulate the process of a drill bit drilling through the bone. The finite element model was set up in the Abaqus6.11; the prediction model of the drilling force was gotten by using the regression orthogonal experiment and data processing software Matlab7.0. Diverse values of drilling speed, feed rate and drill diameter are important factors which will lead to changes in the drilling forces. By controlling the drilling parameters can obtain the optimal drilling force. The results show that the diameter has the greatest influence on the drilling force, the drilling speed the second, the feed rate the last.

A Hybrid Approach to Computer-Aided Process Planning for Prismatic Parts

1994 ◽  
Author(s):  
Y. F. Zhang ◽  
A. Y. C. Nee ◽  
J. Y. H. Fuh
Keyword(s):  
Process Planning ◽  
Hybrid Approach ◽  
Optimization Method ◽  
Optimal Operation ◽  
Operation Sequencing ◽  
Computer Aided Process Planning ◽  
Prismatic Parts ◽  
Minimum Number ◽  
Set Up

Abstract One of the most difficult tasks in automated process planning is the determination of operation sequencing. This paper describes a hybrid approach for identifying the optimal operation sequence of machining prismatic parts on a three-axis milling machining centre. In the proposed methodology, the operation sequencing is carried out in two levels of planning: set-up planning and operation planning. Various constraints on the precedence relationships between features are identified and rules and heuristics are created. Based on the precedence relationships between features, an optimization method is developed to find the optimal plan(s) with minimum number of set-ups in which the conflict between the feature precedence relationships and set-up sequence is avoided. For each set-up, an optimal feature machining sequence with minimum number of tool changes is also determined using a developed algorithm. The proposed system is still under development and the hybrid approach is partially implemented. An example is provided to demonstrate this approach.

Development of Foot Structure for Humanoid Robot Using Topology Optimization

2018 ◽  
Vol 29 ◽  
pp. 34-45
Author(s):  
Van Tinh Nguyen ◽  
Daichi Kiuchi ◽  
Hiroshi Hasegawa
Keyword(s):  
Topology Optimization ◽  
Humanoid Robot ◽  
Differential Evolution Algorithm ◽  
Optimization Method ◽  
Gait Pattern ◽  
Surface Model ◽  
Foot Structure ◽  
Adaptive Differential Evolution ◽  
Reaction Forces ◽  
Set Up

This paper addresses the development of a foot structure for 22-Degree of Freedom (DoF) humanoid robot. The goal of this research is to reduce the weight of the foot and enable the robot to walk steadily. The proposed foot structure is based on the consideration of cases where the ground reaction forces are set up in different situations. The optimal foot structure is a combination of all the topology optimization results. Additionally, a gait pattern is generated by an approximated optimization method based on Response Surface Model (RSM) and Improved Self-Adaptive Differential Evolution Algorithm (ISADE). The result is validated through dynamic simulation by a commercially available software called Adams (MSC software, USA) with the humanoid robot named KHR-3HV belonging to Kondo Kagaku company.

Modelling and Optimization of End Milling Process Using TLBO and TOPSIS Algorithm

2017 ◽  
pp. 54-81 ◽  
Author(s):  
Atul Tiwari ◽  
Mohan Kumar Pradhan
Keyword(s):  
Material Removal Rate ◽  
Material Removal ◽  
Metal Cutting ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Optimization Method ◽  
Depth Of Cut ◽  
Multi Objective ◽  
Order Preference

To assure desire quality of machined products at minimum machining costs and maximum material removal rate, it is very important to select optimum parameters when metal cutting machine tool are used. Minimum Surface Roughness (Ra) is commonly desirable for the component; however Material Removal Rate (MRR) should be maximized. This chapter presents an approach for determination of the best cutting parameters precede to minimum Ra and maximum MRR simultaneously by integrating Response Surface Methodology with Multi-Objective Technique for Order Preference by Similarity to Ideal Solution and Teaching and learning based optimization algorithm in face milling of Al-6061 alloy. 30 experiments have been conducted based on RSM with 4 parameters, namely Speed, Feed, Depth of Cut and Coolant Speed and three levels each. ANOVA is performed to find the most influential input parameters for both MRR and Ra. Later the multi-objective attribution selection method TOPSIS and multi objective optimization method TLBO is used to optimize the responses.

scholarly journals Energy principle and material removal sequence optimization method in machining of aircraft monolithic parts

2020 ◽  
Vol 33 (10) ◽  
pp. 2770-2781
Author(s):  
Yinfei YANG ◽  
Longxin FAN ◽  
Liang LI ◽  
Guolong ZHAO ◽  
Ning HAN ◽  
...  
Keyword(s):  
Material Removal ◽  
Optimization Method ◽  
Energy Principle ◽  
Sequence Optimization

Experimental Non-Linear Model Updating Applied in Cylindrical Journal Bearings

2001 ◽  
Author(s):  
Katia Lucchesi Cavalca ◽  
Sérgio Junichi Idehara ◽  
Franco Giuseppe Dedini ◽  
Robson Pederiva
Keyword(s):  
Linear Model ◽  
Model Updating ◽  
Optimization Method ◽  
Model Parameters ◽  
Numeric Model ◽  
Rotating Systems ◽  
Non Linear ◽  
Symmetric Rotor ◽  
Set Up ◽  
Experimental Values

Abstract The present paper proposes the use of non linear model updating applying unrestricted optimization method, in order to obtain a methodology, which allows the calibration of mathematical models in rotating systems. An experimental set up for this purpose consists of a symmetric rotor, on a rigid foundation supported by two hidrodynamic cylindrical bearings and with a central disk of considerable mass, working as na unbalancing excitation force. Once the numeric and experimental values are obtained, error vectors are defined, which are the minimization parameters, through the variation of the numeric model parameters. The method presented satisfactory results, as it was able to calibrate the mathematical model, and then to obtain reliable responses for the physical system studied. The research also presents a contribution for the rotating machine desing area as it presents a relatively simple methodology on the updating and revalidation of computacional models for machines and structures.

scholarly journals Effect of Formulated Fertilization on Fruit Quality of Early Ripe Peach

2019 ◽  
Vol 136 ◽  
pp. 07016
Author(s):  
Changbing Pu ◽  
Qiao Xiao ◽  
Jin Wang ◽  
Dong Liang ◽  
Xiulan Lv
Keyword(s):  
Fruit Quality ◽  
Orthogonal Experiment ◽  
Organic Fertilizer ◽  
Chemical Fertilizer ◽  
Test Material ◽  
Peach Fruit ◽  
Early Maturing ◽  
Set Up ◽  
Trace Element Fertilizers

Using the early maturing peach variety 'Japan Matsusen' as the test material, nine groups of formula fertilization schemes were set up by orthogonal experiment to study the effects of different fertilization treatments on the quality of peach fruit, in order to obtain the best fertilization formula to improve fruit quality. The results showed that the quality of peach fruit was significantly improved by adding organic fertilizer to the base fertilizer instead of chemical fertilizer. Therefore, by adding organic fertilizer as the base fertilizer, reducing the application amount of chemical fertilizer, and adding other trace element fertilizers can effectively improve the quality of peach fruit.

Parameter Optimization of Laser Scribing Technics of 30Q130 Grain-Oriented Silicon Steel Based on Genetic Neural Network

2010 ◽  
Vol 37-38 ◽  
pp. 844-848
Author(s):  
Yu Huang ◽  
Yong Liu ◽  
Guo Li Zhu
Keyword(s):  
Neural Network ◽  
Orthogonal Experiment ◽  
Core Loss ◽  
Optimization Method ◽  
Silicon Steel ◽  
Laser Scribing ◽  
Cold Rolling And Annealing ◽  
Neural Network Prediction ◽  
Genetic Neural Network ◽  
Network Prediction

A laser is often considered to scribe the grain-oriented silicon steel surfaces after cold-rolling and annealing to reduce the core loss. It is necessary to select the best scribing parameters to maximize the reduction in this process. This paper proposed an optimization method of genetic algorithm during laser scribing of 30Q130 steel, by developing an artificial neural network prediction model using a database form a designed orthogonal experiment. The objective was to determine the best combination values of three important scribing parameters, namely scribing velocity, pulse energy and scanning spacing, that can get the largest core loss reduction. An optimized combination of parameters was obtained by this method and then validated by an adding experiment. The result indicates that the optimization model is reliable.

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