Analysis And Modelling Of Modulation-assisted Turning Process

For CNC machine tools,automatic production lines and flexible manufacturing systems,effective chip controlling serves as a prerequisite to fully exert production capacity and achieve smooth production.In recent years,difficult-to-machine materials,such as titanium alloys and stainless steels,have been widely used in the aerospace,automotive and military industries due to their excellent mechanical properties.However,as the result of their good plasticity and toughness,a large number of continuous and tangled ribbon-shaped chips are generally produced in the process of high-speed and high-efficiency machining.Bulky and hard to handle as they are,these chips may interfere with the proper operation of the cutting process,damage the machined surface of the workpiece,and even threaten the personal safety of the machine tool operator.Therefore,effective chip controlling is an urgent and important issue in the machining process of these materials.Modulation-assisted machining(MAM)technology is one type of vibration-assisted machining technology.By superimposing a sinusoidal tool vibration,with modulatable frequency and amplitude,onto the feed direction of the conventional machining process,the previous continuous machining process can be transformed into discrete machining process.In this case,the tool contacts and loses contact with the workpiece periodically,and discrete chips are generated in controllable lengths.As a result,reliable chip controlling is realized.In addition,there have been experimental results showing that modulation-assisted machining has advantages over conventional machining on the aspects of lowering tool temperature,reducing tool wear,controlling surface texture etc.However,the superimposed tool modulation makes the material removal process more complex during machining,which makes the studies on modulation-assisted machining more difficult.The current studies are mainly qualitative and experimental,while systematic,deep and quantitative studies based on the modelling of the machining process are lacking.For this reason,taking the application of the modulation-assisted machining technology in turning as an example,this thesis is dedicated to studying the method of realizing automatic chip breaking in the turning process by using tool modulation,and building a series of predictive models of surface texture and roughness,cutting forces,tool temperature and tool wear for modulation-assisted turning.Furthermore,based on the proposed predictive models,a multi-objective optimization is performed on the main process parameters of modulation-assisted turning to achieve the purpose of controlling chip length,improving machining quality,reducing tool wear rate and improving machining efficiency etc.The main research contents are as follows:The kinematics of modulation-assisted turning is studied.The cutting path with tool modulation for both cylindrical turning and face turning configurations are analyzed,and a unified criterion for realizing automatic chip breaking is deduced.The length of the undeformed chip and its influential factors are analyzed,which can provide a theoretical basis for chip controlling.By analyzing the forming process of the workpiece machined surface under tool modulation,a predictive model for surface texture and surface roughness is proposed,and the effects of process parameters on the machined surface are analyzed accordingly.Related experiments are carried out to validate the proposed chip length and surface roughness models.The direction of the instantaneous tool feed motion in modulation-assisted turning is analyzed.Accordingly,each modulation cycle is classified into forward feed phase and reverse feed phase,which correspond to different machining mechanisms.By analyzing the shapes of the instantaneous undeformed chip section and the forces acting on the cutting edge,a predictive analytical cutting force model is proposed,which takes into consideration of workpiece material,tool geometry,cutting parameters and modulation parameters.The unknown model parameters are identified through the teaching-learning-based optimization(TLBO)algorithm.Experiments are carried out under different process parameters,from which the cutting forces in modulation-assisted turning are measured.The effects of process parameters on cutting forces are analyzed and the accuracy of the predictive analytical cutting force model is verified.The time-varying heat flux that flows into the tool in modulation-assisted turning is studied.By simplifying the tool geometry to some degree,an analytical model for predicting tool temperature is proposed,and through finite element simulations of the heat conduction and the orthogonal cutting processes,the rationality of the tool geometry simplification is illustrated.Experiments are carried out to measure the tool temperature and tool wear in modulation-assisted turning,and the validity of the tool temperature model is verified directly and indirectly by the experimental results.The tool flank wear rate is further predicted based on the calculated tool average temperature and temperature fluctuation.The method for multi-objective optimization of process parameters in modulationassisted turning is studied.Considering the constrains on chip length,surface roughness,feasible usage boundary of the piezoelectric actuator,an optimization of process parameters is carried out based on the TLBO algorithm for achieving maximal material removal rate and minimal tool wear rate.A series of Pareto optimal solutions are obtained for guiding the machining process.Related experiments are carried out,and via the grey relational analysis of the experimental results,the rankings of the process parameters before and after the optimization are evaluated,through which the optimization method is validated.The methods proposed in this thesis for modelling and parameters optimization of modulation-assisted turning process are universal and can be extended to the conditions with other workpiece materials,tool geometries and process parameters.The research results in this thesis can provide the theoretical basis for the chip controlling,cutting force controlling,tool temperature and tool wear controlling during the modulation-assisted machining process,and have a positive effect on the application and promotion of the modulation-assisted machining technology.