【作者】 王亮；

【导师】 王金娥； 郭旭红；

【作者基本信息】 苏州大学 ， 机械工程（专业学位）， 2015， 硕士

【摘要】 本文针对昆山市鸿利精密五金有限公司铣削Cr12Mo V淬硬钢过程中刀具使用寿命低的问题,通过Φ10非涂层硬质合金立铣刀铣削Cr12Mo V淬硬钢刀具使用寿命的正交试验,建立刀具使用寿命的经验公式,并根据刀具使用寿命的经验公式,结合加工时间和加工成本建立多目标优化模型,运用MATLAB遗传算法工具箱对铣削参数进行优化,旨在通过优化后的铣削参数对企业铣削Cr12Mo V淬硬钢台阶面提供理论指导。本文的主要内容及结论如下:1.通过正交试验的极差法分析了各铣削参数对刀具使用寿命的影响程度,得出以下结论:对刀具使用寿命影响最大的是每齿进给量fz,其次是铣削深度ap,然后是铣削速度v,最后是铣削宽度ae;最优铣削参数组合为:v=70m/min,fz=0.002mm/z,ap=0.4mm,ae=6 mm。2.通过正交试验的方差法分析了各铣削参数对刀具使用寿命影响的显著性,得出以下结论:每齿进给量fz对刀具使用寿命的影响高度显著,铣削深度ap对刀具使用寿命的影响显著,铣削速度v对刀具使用寿命的影响较显著,铣削宽度ae对刀具使用寿命的影响不显著;最优铣削参数组合为:v=70m/min,fz=0.002mm/z,ap=0.4mm,ae=6 mm;验证了极差分析得出的结论是可靠的。3.运用多元线性回归的方法,建立了刀具使用寿命的经验公式:0.8696 1.5707 1.8009 0.08190.1254z p eTuf a a----=通过F检验法得出刀具使用寿命的经验公式是高度显著的;通过刀具使用寿命试验值和经验值的比较得出,最大相对误差为12.08%,最小相对误差为0.31%,平均相对误差为3.61%,刀具使用寿命的经验公式有较高的预测精度,可用于刀具使用寿命的预测。4.采用二维影像测量仪观察铣刀的主要磨损形态与破损形式,得出铣刀侧刃的磨损形态主要是前刀面月牙洼磨损和后刀面磨损;铣刀的破损形式主要是刀尖崩碎。5.以公司实际加工的Cr12Mo V淬硬钢台阶面为研究对象,建立了以最短加工时间、最低加工成本、最大刀具使用寿命为目标函数,铣削速度、每齿进给量、铣削深度、铣削宽度为约束,组合系数法选取加权系数的多目标优化模型,运用MATLAB遗传算法工具箱对铣削参数进行优化,结果表明:以最短加工时间和最低加工成本为优化目标时,加工时间的缩短、加工成本的降低是以刀具使用寿命的降低为代价的;以最大刀具使用寿命为优化目标对企业来说经济意义不大;以综合目标优化时,在刀具使用寿命提高将近一倍的同时,加工时间缩短了1.10%,加工成本降低了6.98%,表明综合目标优化后的铣削参数在解决企业实际问题的同时,还能缩短加工时间、降低加工成本;最优铣削参数组合为:v=99.910m/min,fz=0.002mm/z,ap=0.400mm,ae=6.018mm。更多还原

【Abstract】 This thesis aims at studying the problems of the low tool life in milling Cr12 Mo V hardened Steel in K unshan Hongli Precision Hardware Co.,. The tool life model was established by the orthogonal test of tool life in milling Cr12 Mo V hardened steel with non-coated carbide end which diameter is 10 mm, and according to the tool life model to set up the multi-objective optimization model with processing time and processing costs, using genetic algorithm for optimization of milling parameters to provide theoretical guidance for enterprise end milling of hardened Cr12 Mo V steel surface. The main contents and conclusions of this thesis are as follows:1. The range of orthogonal tests show that the feed per tooth has the largest influence on tool life, and then is the milling depth, and then is the milling speed,and milling width has the smallest influence. The optimal milling parameters is v=70m/min, fz=0.002mm/z, ap=0.4mm, ae=6mm.2. The variance analysis of orthogonal tests show that the per tooth has the largest impact on tool life, and then is the milling depth, and then is the milling speed,and milling width has the smallest impact. The optimal milling parameters is v=70m/min,fz=0.002mm/z,ap=0.4mm,ae=6mm. The conclusion of The range analysis is reliable by analysis on variance.3. The tool life predictive model T=0.1254v-0.8696 fz-1.5707ap-1.8009ae-0.0819 is established by multiple linear regression analysis, and proved to believable by analysis on variance. The Comparisons of the tool life measured value and theoretical model predictive shows that the maximum error is 12.08%, the minimum error is 0.31%, the average error is 3.61%,so the established model is highly significant with high confidence.4. The tool dominant wear morphologies and breakage form were examined by image measuring instrument, the dominant wear morphologies is rank face wear and flank wear and the dominant breakage form is chipping.5. Taking step surface of Cr12 Mo V hardened steel as the research object,based on the targets of manufacturing time, manufacturing cost, tool life optimization model, according to research of the high, constraints of milling speed, feed per tooth, milling depth milling width, setting up multi-objective optimization model of weighted coefficient, system. Using genetic algorithm toolbox of MATLAB to optimize the milling parameters, the results shows that: take manufacturing time and manufacturing cost as optimization goal, the shortening of the time and the reduction of cost is at the cost of reduction of tool life, take tool life as the optimization goal has not economic significance to the enterprise; and optimize the multi-objectives, the tool life improved nearly doubled, processing time is reduced by 1.10% and the processing cost is reduced by 6.98%, which shows that milling parameters after optimization can solve the real problem,shorten the processing time, reduce the processing cost, the optimal milling parameter is v=99.910m/min, fz=0.002mm/z, ap=0.400 mm, ae=6.018 mm.更多还原