Study On Tool Wear Mechanism And Model Establishment In High-speed Milling Of 300M Steel With Cryogenic Minimum Quantity Of Lubricant

Cryogenic Minimum Quantity of Lubricant(CMQL)inherits to the environmental protection,safety and harmless,reduce costs and technological requirements.Combining micro-lubrication(MQL)with low-temperature cold air,and the compressed air is mixed with a very small amount of cutting oil mist during processing and is sprayed to the processing point.It would suppress the temperature rise in the contact area between "tool-chip" and "tool-workpiece",alleviate the phenomenon of tool sticking,improve tool wear and improve machining accuracy,especially in the field of difficult machining.Especially in the field of hard-working materials,the effect is more significant.300 M steel unique high strength,corrosion resistance and other excellent performance gradually recognized by the world and because of serious tool wear and low processing quality,it has been unable to rely on dry or traditional wet method to complete 300 M steel high-quality processing needs.In view of the processing characteristics of 300 M steel,this thesis studied the tool wear of 300 M steel with low temperature and micro-lubrication and high speed milling.First of all,the comparison test in High-speed Milling of 300 M Steel with Cryogenic Minimum Quantity of Lubricant for different tool coating materials was carried out,and this thesis have preferred the tool coating materials suitable for Cryogenic Minimum Quantity of Lubricant processing conditions.The thesis conducted a CMQL one-factor experiment with the preferred tool different process parameters,and the optimal combination of CMQL process parameters is determined by the index of tool wear and surface roughness.Secondly,based on the optimal process parameters of CMQL,the single factor test of tool wear for high speed CMQL milling of 300 M steel was carried out,and the thesis study the effect of cutting parameters and tool tip corner radius on tool wear.The wear status of the tool was observed and compared with the dry cutting,and The mechanism of tool wear under CMQL is analyzed.Thirdly,based on the test results of single factor,and a more reasonable cutting parameter was selected to carry out the orthogonal test of tool wear.The flank face wear prediction model was established based on orthogonal test data and empirical formula,and the significance test was carried out.The genetic algorithm is used to optimize the cutting parameters for the final target with a minimum amount of tool wear when the metal removal is maximized.Finally,the Deform simulation software was used to simulate the machining conditions of high speed milling 300 M steel under CMQL conditions.The thesis compared the experimental and simulation results for the wear morphology and wear amount of rake face and flank face,and completed the simulation prediction of tool wear.