Tool Wear And Surface Integrity Of Titanium Alloy Milling

Titanium alloy is one of the most valuable strategic metal material in the21thcentury, and it is the essential material in the aerospace field. Serious tool wear, poormachined surface quality and low machining efficiency have become the mainproblems restricting the development of titanium alloy. Research on the mechanism oftool wear and surface quality in titanium alloy cutting process and optimizing propercutting parameters are of important significance in aerospace field.The laws of tool life influenced by milling parameters were studied in titaniumalloy milling process under rough and finish machining conditions, and predictionmodels of tool life were established under the rough and finish machining conditions.The tool wear mechanism and breakage form were analysed, and the methods wereproposed to improve the tool wear.The laws of cutting force and cutting temperature influenced by cuttingparameters, cooling conditions and tool wear were studied in machining process, andprediction models of cutting force and cutting temperature were established. The size,property and influence depth of residual stress in surface layer influenced by coolingconditions, milling parameters and tool wear were analysed, and residual stressprediction models influenced by milling parameters were established. The mechanismof surface residual stress was discussed based on the milling force and millingtemperature obtained from the experiments.The laws of surface roughness influenced by cooling conditions, cuttingparameters and tool wear were analysed, and the prediction models of surfaceroughness under different machining conditions were established. The theory modelsof surface roughness were established and discussed based on the material propertyand milling process.The change laws of surface layer metallographic structure and microhardnessinfluenced by milling parameters and tool wear were analysed, and the formationmechanism of surface layer microhardness was discussed. The experimental resultsshow that phase transition was taken place with the increase of milling speed.Different multi-objective optimization models were established with the millingparameters as design variables, material removal rate, tool life and material removalrate, surface roughness, surface residual stress as the objective functions, respectively.The milling parameters which meet the different optimization models were obtained by the genetic algorithm and the optimization results were verified by the millingexperiments. Experimental results show that the optimization results are in goodreliability.