Analytical Modeling And Optimizing Of Cutting Energy And Machining Performances In Dry Whirling Milling Based On Material Removal Mechanism

Screw dry whirling milling is a promising alternative machining process for traditional process,such as turning,griding,to produce the long and slender screw parts(e.g.,worm and ball screws).This process offers numerous advantages such as better surface quality than milling,high productivity,dry cutting without coolants,which is widely used by manufacturers in machining precision screw parts made of hard materials(e.g.,titanium alloy and quenched steel)for many mechanical industries such as machine tool,automobile and aviation.At present,the machining mechanism and process performance of the cutting process and the energy consumption of the cutting process are mainly focused on the traditional cutting process,such as turning,milling etc.However,for the dry whirling milling with combined motion of the tools and the workpiece,multi-tools cutting and variable intermittent cutting characteristics,research on the milling mechanism,energy and process performance modeling has been rarely studied,especially the research on collaborative optimization of energy consumption and process performances is lack of clear investigation,which restrict the development of high efficiency,high quality and green dry whirling milling technology in China.In this thesis,the analytical modeling of cutting energy and optimization of machining performances in dry whirling milling based on material removal mechanism are presented.The research contents including analytical modeling of material removal mechanism in dry whirling milling,cutting energy modeling based on material removal mechanism,collaborative optimization of energy consumption and process performances are carried out.The detailed main research work of this thesis is listed as follows:Firstly,an analytical approach to investigate the material removal mechanism in whirling milling is presented,thus to predict the undeformed chip geometry,material removal rate(MRR),cutting forces.Based on combined motion of the tools and the workpiece,the analytical kinematics of whirling milling is established to understand the the coordinate conversion relationship between the tool and the workpiece coordinate system.The varying tool-workpiece engagement geometry along the cutting trajectory is identified to model the varying undeformed chip geometry including instantaneous chip thickness,cross-section area and tool-workpiece contact length and cutting force.Secondly,an analytical model for predicting cutting energy based on the material removal mechanism of whirling milling is presented.Then,the cutting parameters affecting the specific cutting energy(SCE)characteristics are identified considering the un-deformed chip formation.An analytical model is developed as functions of the identified cutting parameters by calculating material removal volume and cutting forces.the effects of cutting parameters and material removal rate(MRR)on SCE were investigated and analyzed,which can provide valuable information and guidance for the optimal selection of cutting parameters to minimize SCE and improve MRR.Thirdly,the modeling and analysis of machining performances based on the the material removal mechanism of whirling milling are investigated.The infuences of cutting parameters on material removal rate are analyzed by using the above analytical MRR model.Then,the form errors including circularity error,scallop height are investigated and predicted as a function of tools and workpiece motion,position and dimension parameters,which are used to develop the screw surface roughness predictive model.The whirling milling experiments were conducted to validate the analytical model.The influences of cutting parameters on machining performances(e.g.,surface roughness and MRR)are finally analyzed to explore the potential of productive cutting conditions for whirling milling.Finally,although one of the multiple machining performances of dry whirling milling can be optimized,this could not always guarantee the improvement of another.Hence,the multi-objective collaborative optimization of cutting parameters is presented to balance and simultaneously optimize the whirling milling performances,namely,SCE,cutting force,MRR,surface roughness etc.The integrated Taguchi,Grey relational analysis and principal component analysis method is applied to transform the multiple performances into a signal grey relational grade(GRG).The multi-objective optimization mathematical model of GRG is developed as a function of the cutting parameters based on the response surface methodology to determine the optimal parameter combinations.