Multi-Objective Optimization Of CNC Turning Process Parameters Based On Response Surface Method And Artificial Bee Colony Algorithm

With the rapid development of the times,the world energy crisis has become more and more serious.As the foundation of the world industrial revolution and the foundation of my country's economic development,the manufacturing industry has promoted social productivity and created huge wealth for people,along with huge consumption of energy.Compared with developed countries,my country's manufacturing industry still has a lot of room for development.The efficiency and quality improvement of manufacturing are still problems to be solved by manufacturing enterprises.For the rise of Made in China and to respond to the call to protect the environment and save energy on the basis of vigorously developing the economy,green manufacturing has become the theme of the new era.Numerical control machine tools in the manufacturing industry have a large volume and a wide range.Research on the multi-objective optimization of the process parameters of numerical control machine tools can improve the competitiveness of enterprises and promote my country's economic development.It is also in line with my country's slogan of energy saving and emission reduction.It has important research significance.First of all,green manufacturing puts forward new requirements for energy conservation,product quality,and production efficiency in the production process.Optimizing the process parameters of CNC machine tools plays a vital role in the green development of the manufacturing industry.The optimization problem under a single objective cannot meet the actual needs of the manufacturing industry.Multi-objective optimization of process parameters considering energy consumption has become the main research direction.Secondly,the energy consumption of CNC machine tools varies greatly in different processing time periods,and traditional energy consumption modeling is complicated and difficult to operate.The response surface method can connect the complex unknown relationship between variables,and fit a simple first-order or second-order polynomial model in a certain area.This paper treats the CNC turning process as a whole,and directly studies the influence of different combinations of process parameters on the total power of each period.Using statistical regression theory,the function model of process parameters and energy consumption is established,and finally through analysis of variance Determine the accuracy of the regression equation.Finally,in the process parameter optimization method,the traditional solution method cannot be applied to the new multi-objective problem.Genetic algorithm,particle swarm algorithm and artificial bee colony algorithm have their own advantages and disadvantages.When solving the continuous multi-objective optimization model of process parameters,this paper improves the artificial bee colony algorithm based on the individual replacement criteria of Pareto dominance and crowding distance,and verifies it by the epsilon accurate solution algorithm.The improved artificial bee colony algorithm has good results,and the obtained multi-objective solution set scheme provides a variety of choices for the operator to make decisions,and provides a scientific basis for realizing the optimization of manufacturing CNC turning process parameters for green manufacturing.