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IEEE 6th International Congress on Big Data (BigData Congress)

作者： Wang, Chen Wang, Yi Wang, KeSheng Dong, Yao Zhou, Xueling Wang, Shenghuai Shanghai Univ Shanghai Key Lab Intelligent Mfg & Robot Shanghai Peoples R China Hubei Automot Ind Inst Dept Mech Engn Shiyan Peoples R China Univ Manchester Sch Met Manchester Lancs England

ISBN: (纸本)9781538619964

At present, it is an important method to solve the problem of industrial multi-objective optimization based on data-driven evolutionary, optimization. In this paper, we study the multi-objective optimization problem of CNC cutting based on data-driven teaching and learning based optimization algorithm. Based on the large-scale off-line CNC cutting data to establish the optimization model, using the improved teaching and learning based optimization algorithm (ITLBO) to solve The simulation experimental results show that the optimization results are better.

关键词： big data driven evolutionary computation cutting parameters optimization teaching and learning algorithm

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Surface topography analysis and cutting parameters optimization for peripheral milling titanium alloy Ti-6Al-4V

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INTERNATIONAL JOURNAL OF REFRACTORY METALS & HARD MATERIALS 2015年 51卷 192-200页

作者： Yang, Dong Liu, Zhanqiang Shandong Univ Sch Mech Engn Jinan 250061 Peoples R China Shandong Univ Minist Educ Key Lab High Efficiency & Clean Mech Mfg Jinan 250061 Peoples R China

This paper presents the effect of cutting parameters (cutting speed, feed rate and radial depth of cut) on surface topography in peripheral milling of titanium alloy Ti-6Al-4V. Peripheral milling experiments based on the Taguchi method have been conducted on Ti-6Al-4V to characterize surface topographies by various milling conditions. Surface analysis techniques including surface defects, multiple linear regression analysis of surface parameters and auto-correlation analysis of the surface profile, were implemented to characterize the machined surface topography. The experimental results have shown that the main forms of surface defect in peripheral milling of Ti-6Al-4V are feed marks, scratch marks, adhered material particles, etc. The high quality of the machined surface can be obtained in the combined conditions with high cutting speed, low feed and small radial depth of cut. Auto-correlation analysis is used to describe the spatial relation dependence of the surface topography, the direction and periodicity of the surface texture. Increasing cutting speed is helpful to reduce the random components in the auto-correlation spectra of the machined surfaces. However, increasing feed rate has the opposite effect Radial depth of cut has no significant influence on auto-correlation spectra in finish milling. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Surface topography cutting parameters optimization Peripheral milling Ti-6Al-4V

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Study on high-speed cutting parameters optimization of AlMn1Cu based on neural network and genetic algorithm

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ADVANCES IN MECHANICAL ENGINEERING 2016年第4期8卷 1-12页

作者： Wang, Zhenhua Yuan, Juntang Yin, Zengbin Li, Chao Nanjing Univ Sci & Technol Sch Mech Engn 200 Xiao Ling Wei St Nanjing 210094 Jiangsu Peoples R China

In this article, the cutting parameters optimization method for aluminum alloy AlMn1Cu in high-speed milling was studied in order to properly select the high-speed cutting parameters. First, a back propagation neural network model for predicting surface roughness of AlMn1Cu was proposed. The prediction model can improve the prediction accuracy and well work out the higher-order nonlinear relationship between surface roughness and cutting parameters. Second, considering the constraints of technical requirements on surface roughness, a mathematical model for optimizing cutting parameters based on the Bayesian neural network prediction model of surface roughness was established so as to obtain the maximum machining efficiency. The genetic algorithm adopting the homogeneous design to initialize population as well as steady-state reproduction without duplicates was also presented. The application indicates that the algorithm can effectively avoid precocity, strengthen global optimization, and increase the calculation efficiency. Finally, a case was presented on the application of the proposed cutting parameters optimization algorithm to optimize the cutting parameters.

关键词： High-speed milling cutting parameters optimization neural network genetic algorithm surface roughness AlMn1Cu

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cutting parameters optimization of Thin-walled Workpiece Based on PSO and FEM

Cutting Parameters Optimization of Thin-walled Workpiece Bas...

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2012 International Conference on Mechanical Materials and Manufacturing Engineering(ICMMME 2012)

作者： Qian Lili Chen Weifang Ma Wantai College of Mechanical and Electrical Engineering Nanjing University of Aeronautics and Astronautics

An approach to optimize the cutting parameters based on Particle Swarm Algorithm(PSO) and Finite Element Method(FEA) was proposed. A cutting parameters optimization model was established whose design variables are the cutting parameters and objective function is to minimize the maximum deformation. PSO was used to optimize the cutting parameters and FEA was utilized to predict the machining deformation of the thin-walled workpiece. Finally, the entire technique was demonstrated in a case study. The simulation and experimental results show that the approach can be further employed into the practical machining situation.

关键词： cutting parameters optimization Particle swarm algorithm Deflection control Thin-walled part Finite Element Method

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A Research on NC Machining cutting parameters optimization

A Research on NC Machining Cutting Parameters Optimization

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International Conference on Information Sciences,Machinery,Materials and Energy（ICISMME 2015）

作者： Wei Tang Guangrong Yan Xiangyu Xu Dan Yu Zaijun Wang Hongzhen Chu Beijing University of aeronautics and astronautics Department of Mechanical Engineering and Automation Shenyang Aircraft Corporation

This paper presents an effective method of NC machining cutting parameters *** a given machine NC code,we use the secondary development tools provided by VERICUT software,the time series segmentation algorithm of sliding window technique,back stepping method for getting the feed rate based on the empirical formula and other methods to extract,process and optimize the cutting *** a result of these,we can make the output power of the spindle reaching smooth and get the optimized processing code finally.

关键词： cutting parameters optimization Simulation of cutting in VERICUT Output power smoothing

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An integrated multi-objective optimization approach to determine the optimal feature processing sequence and cutting parameters for carbon emissions savings of CNC machining

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INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING 2020年第6期33卷 609-625页

作者： Tian, Changle Zhou, Guanghui Lu, Fengyi Chen, Zhenghao Zou, Liang Xi An Jiao Tong Univ Sch Mech Engn Xian Peoples R China Xi An Jiao Tong Univ State Key Lab Mfg Syst Engn Xian Peoples R China

Carbon emissions caused by CNC machining attract increasing attentions. It has been proved that carbon emissions and processing time are jointly affected by process routes and cutting parameters. cutting parameters and process routes optimization, however, are traditionally carried out separately and sequentially, limiting the potential of carbon emissions reduction. To further reduce carbon emissions, an integrated approach of features processing sequence and cutting parameters optimization is proposed to minimize the carbon emissions and processing time. Firstly, a multi-objective optimization model for minimizing carbon emissions and processing time is proposed. Secondly, an NAGS-II algorithm is designed to solve the proposed model. Then, case studies are conducted to verify the feasibility and validity of the proposed integrated optimization approach. Case studies and comparative analysis with other literature show that: i) integrated optimization of features processing sequence and cutting parameters can achieve more carbon emissions savings than features processing sequence optimization with preset cutting parameters;ii) the proposed multi-objective integrated optimization method can strike a trade-off between carbon emissions and processing time.

关键词： Process routes optimization cutting parameters optimization integration optimization low-carbon manufacturing

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optimization of cutting parameters considering tool wear conditions in low-carbon manufacturing environment

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JOURNAL OF CLEANER PRODUCTION 2019年第Jul.20期226卷 706-719页

作者： Tian, Changle Zhou, Guanghui Zhang, Junjie Zhang, Chao Xi An Jiao Tong Univ Sch Mech Engn Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ State Key Lab Mfg Syst Engn Xian 710054 Shaanxi Peoples R China

Carbon emissions have drawn widely attention due to the worsening climate changes. In a machining process, a reasonable selection of cutting parameters can not only save the production cost and time, but also reduce the production carbon emissions. In addition, the wear conditions of different cutting tools also have great influence on cutting parameters selection as they could cause huge difference on carbon emissions. However, in traditional optimization methods of cutting parameters, the tool wear conditions are always ignored. Thus, in order to overcome this limitation, an optimization method of cutting parameters considering the tool wear conditions is developed. Firstly, the quantified relationships among cutting parameters, tool wear and production indexes (production carbon emissions, cost and time) are analysed. Then, a multi-objective cutting parameters optimization model is established based on the above production indexes to determine the optimal cutting parameters and tools. Thirdly, a modified NSGA-II algorithm is used to resolve the proposed model. Finally, a case study is designed to demonstrate the advantages and feasibility of the proposed approach. The results show that (i) the optimal cutting parameters change with the tool wear conditions;(ii) For the same type of cutting tools with different wear conditions, the optimal values of production carbon emissions, cost and time increase along with the raise of the tool wear conditions;(iii) For different available cutting tools with different tool wear conditions, it is necessary to apply a multi-objective optimization method to decide the optimal production carbon emissions, cost and time. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Low-carbon manufacturing cutting parameters optimization Tool wear condition NSGA-II algorithm Game theory

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Integrated optimization of cutting parameters and scheduling for reducing carbon emissions

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JOURNAL OF CLEANER PRODUCTION 2017年 149卷 886-895页

作者： Zhang, Yi Liu, Qiong Zhou, Yingdong Ying, Baosheng Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China Wuhan Univ Sci & Technol Sch Automobile & Traff Engn Wuhan 430081 Peoples R China

In order to reduce carbon emissions in manufacturing processes and overcome the limitations of previous researches which optimized cutting parameters and scheduling independently and ignored their comprehensive effects on carbon emissions, an integrated optimization model of cutting parameters and scheduling is proposed to minimize completion time and carbon emissions in manufacturing processes. The proposed integrated model is based on the facts that machining time, cutting-tool wear and energy consumption of machine tools depend on cutting parameters, and further affect scheduling aiming at minimizing completion time and carbon emissions in manufacturing processes. Since cutting parameter optimization is a continuous optimization problem but scheduling optimization is a discrete optimization problem, it is very difficult to optimize both simultaneously. Therefore, an improved multi-objective gravitational search algorithm with a strong global search capability which combines crossover and mutation operators is designed to solve the proposed model. Any solution in the search space consists of two parts, cutting parameters and job sequence. They are optimized simultaneously in each iteration in the proposed algorithm. Finally, three workpieces to be processed in two machines including turning and milling are taken as an example. It shows that the proposed integrated optimization can further reduce 2.9 percent of carbon emission and the 2.56 percent of completion time comparing to the traditional separated optimization. The validity of the proposed model and algorithm is verified by computational results. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Carbon emissions cutting parameters optimization Scheduling Gravitational search algorithm

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SELECTION OF PRECISION MACHINING cutting parameters VIA A MODIFIED EFFICIENT GLOBAL optimization APPROACH

SELECTION OF PRECISION MACHINING CUTTING PARAMETERS VIA A MO...

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ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC/CIE)

作者： Aly, Mohamed Hamza, Karim Shalaby, Mohammed Nassef, Ashraf O. Amer Univ Cairo Dept Mech Engn Cairo Egypt Univ Michigan Dept Mech Engn Ann Arbor MI 48109 USA Gen Elect Global Res Struct Lab Niskayuna NY 12309 USA

ISBN: (纸本)9780791855898

The primary objective in precision machining is usually to attain excellent dimensional accuracy and surface finish. In addition, complimentary objectives such as cost and production rate are also important. Proper selection of cutting parameters can profoundly affect both primary and secondary machining performance objectives. While simplified and/or empirical models exist for machining processes, none of those models provides accurate prediction of the dynamic cutting forces, which in turn govern the obtainable quality of the machined surfaces. Finite element analysis (PEA) via ABAQUS/Explicit is adopted in this paper for predicting the machining dynamic cutting forces. Rake and clearance angles, as well as cutting speed are set as the design variables for optimization. Since the machining model requires significant computational resources, economizing the number of FEA runs is desirable. The optimization approach adopted is based off Efficient Global optimization (EGO), where Kriging models are trained to predict the underlying behavior of the machining process via a finite set of sample points. New sample points are then generated via a multi-objective genetic algorithm that seeks locations of optima and/or high uncertainty in the Kriging models. Machining performance of the new samples is then evaluated via FEA, the Kriging models are re-trained and the process is repeated until one of termination criteria is met. The application study presented is an orthogonal cutting test for ultra-precision micro-cutting using diamond tools.

关键词： Precision machining cutting parameters optimization tool selection global optimization

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Evaluation and optimization Method of High Speed cutting parameters Based on cutting Process Simulation

Evaluation and Optimization Method of High Speed Cutting Par...

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2nd International Conference Intelligent Robotics and Applications

作者： Wu, Zhijun Xu, Daochun Feng, Pingfa Yu, Dingwen Zhang, Chenglong Tsinghua Univ Dept Precis Instruments & Mechanol Beijing 100084 Peoples R China

ISBN: (纸本)9783642108167

The choice of reasonable cutting parameters is very important for the application of high speed cutting technology. cutting parameters optimization is a contradiction optimization problem of multi-objectives including cutting efficiency, tool wear and machining quality etc. In order to simplify the complicated problem, a new dimensionless comprehensive evaluation method of cutting parameters based on cutting multi-dimension characteristics including cutting force, temperature, feed rate and cutting depth is put forward in the paper. Then multi-level weight decomposition method is applied to determine the evaluation factors. The relations between multi-objectives and cutting force and temperature are emphatically analyzed. In combination with cutting process physical FEA (finite element analysis) simulation, the effect laws of cutting parameters to cutting force and temperature is researched. Furthermore cutting parameters are evaluated and optimized through the established comprehensive evaluation method. As shown the results: The results obtained by comprehensive evaluation method are match with the results by plenty of cutting experiments. The comprehensive evaluation method is suitable for actual productionapplication because of its simple, effective and extensive characteristics.

关键词： cutting parameters optimization comprehensive evaluation method high speed cutting cutting force cutting temperature

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