Surface Quality And Processing Efficiency Optimization Of Robot Deburring

Die-casting aluminum alloys have the characteristics of light weight,good electrical conductivity and strong casting processability,and are widely used in the die-casting industry.How to polish and polish die-casting parts is getting more and more attention.Nowadays,the grinding of the die-casting parts is mainly done by manual hand-held grinding tools.This method is not only inefficient,but also has unstable processing quality and high cost.With the maturity of robot technology,Gradually there are robotic clamping cutters or rotating boring tools to complete the automatic machining system for the grinding of die castings.However,there are still few guiding theories related to it,which cannot meet the needs of enterprises at this stage.Based on the actual needs,this thesis studies the key technologies such as surface quality and processing efficiency in the deburring process of robots by theoretical research,simulation analysis and experiment,which provides a reference for the actual robot milling die casting.Firstly,the forming mechanism of milling surface and the factors affecting the surface forming quality were analyzed,and determine to study the variation of surface roughness from the perspective of milling parameters and milling force.In order to understand the surface forming mechanism and machining characteristics of milling intuitively,the dynamic finite element simulation model of milling was established.The simulation results show that the maximum stress on the surface of the workpiece is mainly distributed in the first deformation zone,and the chips are curled,similar to the chips produced by actual machining.Secondly,based on the micro-element method,the instantaneous milling force model of milling force is established,and the robot milling experimental platform is built.The silicon-aluminum alloy is used as the processing object.The instantaneous milling force model coefficient is obtained by the average milling force identification test.Experimental results show that the model error is within an acceptable range.Then,the robot milling deburring surface quality experiment is designed.The single factor experiment results show that the surface roughness decreases with the increase of the spindle speed,and becomes larger as the feed per tooth,milling width and milling depth increase.The orthogonal experiment results show that the spindle speed has the greatest influence on the surface roughness,followed by the feed per tooth and the milling depth.The milling width has the least influence.The significant order of the different factors on the experimental results is:spindle speed>feed per tooth>milling depth>milling width;and established empirical model of surface roughness,the model error is within the acceptable range,which has certain guiding significance for actual machining;then the relationship between milling force and surface quality under cutting parameters is analyzed based on milling force model.It shows that the surface roughness increases with the increase of Fx,F y and F z?Finally,the milling efficiency of the robot is optimized from the aspects of cutting parameter optimization and machining path optimization.The cutting parameter optimization model with material removal rate optimization target is established.The genetic algorithm is used to solve the optimal cutting parameter of the robot.The parameter increases the material removal rate from 52.5mm~3/s to 234.3mm~3/s.Secondly,the path optimization problem in this thesis is transformed into atypical generalized business travel problem,and the path optimization model is established.Finally,the best path is obtained by the ant colony algorithm.It shows that when the robot processing speed is 60mm/s and 100mm/s,the processing time is shortened by 7.2s and 4.7s,respectively.