Data-Driven Cutting Parameters Optimization Method in Multiple Configurations Machining Process for Energy Consumption and Production Time Saving

2021 ◽  
Author(s):  
Xikun Zhao ◽  
Congbo Li ◽  
Xingzheng Chen ◽  
Jiabin Cui ◽  
Bao Cao
Keyword(s):  
Energy Consumption ◽  
Cutting Parameters ◽  
Optimization Method ◽  
Parameters Optimization ◽  
Machining Process ◽  
Data Driven ◽  
Production Time ◽  
Time Saving ◽  
Cutting Parameters Optimization ◽  
Multiple Configurations

Cutting Parameters Optimization by Using Particle Swarm Optimization (PSO)

2007 ◽  
Vol 10-12 ◽  
pp. 879-883 ◽  
Author(s):  
Jian Guang Li ◽  
Ying Xue Yao ◽  
Dong Gao ◽  
Chang Qing Liu ◽  
Zhe Jun Yuan
Keyword(s):  
Particle Swarm Optimization ◽  
Essential Role ◽  
Particle Swarm ◽  
Cutting Parameters ◽  
Fundamental Principle ◽  
Parameters Optimization ◽  
Machining Process ◽  
Swarm Optimization ◽  
Cutting Parameters Optimization ◽  
Cutting Experiments

Cutting parameters play an essential role in the economics of machining. In this paper, particle swarm optimization (PSO), a novel optimization algorithm for cutting parameters optimization (CPO), was discussed comprehensively. First, the fundamental principle of PSO was introduced; then, the algorithm for PSO application in cutting parameters optimization was developed; thirdly, cutting experiments without and with optimized cutting parameters were conducted to demonstrate the effectiveness of optimization, respectively. The results show that the machining process was improved obviously.

Machinability Evaluation of Difficult-to-Cut Materials Based on Variable Processing Cost per Unit Material

2011 ◽  
Vol 418-420 ◽  
pp. 1900-1905
Author(s):  
Xun Li ◽  
Jian Ting Wu
Keyword(s):  
Evaluation System ◽  
Cutting Parameters ◽  
Parameters Optimization ◽  
Machining Process ◽  
Cutting Mechanism ◽  
Processing Cost ◽  
Depth Analysis ◽  
Cutting Parameters Optimization ◽  
The Impact ◽  
Variable Processing

Cutting mechanism and characteristics of difficult-to-cut materials have a great difference. Currently, systems or indicators of the machinability are so many that we do not know how to utilize them. Not only because there is no consideration the impact of cutting conditions and parameters on machinability, but they are not be accurate quantitative responses to the machinability of workpiece materials, especially to the difficult-to-cut materials. Based on in-depth analysis of cutting mechanism and objective functions of cutting parameters optimization, an innovative machinability evaluation system based on the variable processing cost per unit material is developed. And the economics of machining process are introduced to the machinability evaluation system. Several classic analysises and calculation examples of the machinability of several typical difficult-to-cut materials have been presented at the end of paper to give a clear picture from the application of the system. The result demonstrates that the machinability evaluation system based on the variable processing cost per unit material has good practicability and maneuverability.

Cutting Parameters Optimization for Constant Cutting Force in Milling

2007 ◽  
Vol 10-12 ◽  
pp. 483-487 ◽  
Author(s):  
Hang Zhao ◽  
Jian Guang Li ◽  
Ying Xue Yao ◽  
Chang Qing Liu
Keyword(s):  
Cutting Force ◽  
Cutting Parameters ◽  
Parameters Optimization ◽  
Machining Process ◽  
Swarm Optimization ◽  
Virtual Machining ◽  
Machining Economics ◽  
Constant Cutting Force ◽  
Optimum Cutting ◽  
Cutting Parameters Optimization

Due to cutting parameters playing an important role in machining economics and machining qualities, much attention has been paid to select optimum cutting parameters. In this paper, cutting parameters optimization for constant cutting force was discussed based-on virtual machining comprehensively. Particle swarm optimization (PSO) was used to seek for the optimal spindle speed and feed rate. The framework of virtual machining based cutting parameters optimization was established. Then two controlled experiments were conducted to demonstrate the effectiveness of cutting parameters optimization both with physical cutting and computer simulation. The results of experiments show that machining process with constant cutting force can be achieved via cutting parameters optimization based on virtual machining.

Cutting Parameters Optimization of Thin-Walled Workpiece Based on Deflection Control

2009 ◽  
Vol 407-408 ◽  
pp. 448-451
Author(s):  
Wei Fang Chen ◽  
Jiu Hua Xu ◽  
Zheng Hua Shen ◽  
Hua Chen
Keyword(s):  
Genetic Algorithm ◽  
Finite Element Method ◽  
Finite Element ◽  
Iterative Method ◽  
Cutting Parameters ◽  
Optimization Method ◽  
Parameters Optimization ◽  
Prototype System ◽  
Thin Walled ◽  
Cutting Parameters Optimization

Thin-walled workpiece is prone to produce deformation in the process of machining because of cutting and clamping forces. In this paper, a model of cutting parameters optimization is proposed to control the deflection. The influence of deflection on nominal milling depth is taken into account and the machining deflection is computed by iterative method. Based on the optimization model, a prototype system is developed to optimize the cutting parameters for a thin-walled workpiece with the genetic algorithm and finite element method. Finally, a simulation example is used to demonstrate the feasibility of the cutting parameters optimization method. The simulation result can be further employed into practical machining situation.

scholarly journals Energy efficient cutting parameter optimization

2021 ◽  
Author(s):  
Xingzheng Chen ◽  
Congbo Li ◽  
Ying Tang ◽  
Li Li ◽  
Hongcheng Li
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Parameter Optimization ◽  
Energy Efficient ◽  
Cutting Parameters ◽  
Machining Process ◽  
Cutting Fluid ◽  
Current Status ◽  
Cutting Parameter ◽  
Cutting Parameter Optimization

AbstractMechanical manufacturing industry consumes substantial energy with low energy efficiency. Increasing pressures from energy price and environmental directive force mechanical manufacturing industries to implement energy efficient technologies for reducing energy consumption and improving energy efficiency of their machining processes. In a practical machining process, cutting parameters are vital variables set by manufacturers in accordance with machining requirements of workpiece and machining condition. Proper selection of cutting parameters with energy consideration can effectively reduce energy consumption and improve energy efficiency of the machining process. Over the past 10 years, many researchers have been engaged in energy efficient cutting parameter optimization, and a large amount of literature have been published. This paper conducts a comprehensive literature review of current studies on energy efficient cutting parameter optimization to fully understand the recent advances in this research area. The energy consumption characteristics of machining process are analyzed by decomposing total energy consumption into electrical energy consumption of machine tool and embodied energy of cutting tool and cutting fluid. Current studies on energy efficient cutting parameter optimization by using experimental design method and energy models are reviewed in a comprehensive manner. Combined with the current status, future research directions of energy efficient cutting parameter optimization are presented.

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