磨床冷却系统的可靠性建模及评估研究
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摘要
对某厂的MKS系列数控磨床的冷却系统的故障数据进行处理,绘制冷却系统故障间隔时间分布函数散点图以及分布密度函数散点图,利用参数估计以及数据拟合确定冷却系统模型的所属分布类型为指数分布。根据所属分布类型确定冷却系统的平均故障间隔时间MTBF,计算冷却系统的平均维修时间MTTR,进而计算冷却系统的固有可用度A。所得结果已经反馈到生产厂家,并获得认可,对数控磨床可靠性的提升有重要意义。
The cooling system failure data of the MKS CNC grinding machine was processed,the scatter plot of the distribution function and the scatter plot of the distribution density function of the cooling system were drawn,and parameter estimation and data fitting were utilized to determine that the model of cooling system is exponential distribution. According to the distribution type,the mean time between failures( MTBF) and the maintenance time to repair( MTTR) of the cooling system were calculated,and then the inherent availability( A) of the cooling system could be determined. The results had been fed back to the manufacturer and approved. It is significant to improve the reliability of the CNC grinding machine.
The cooling system failure data of the MKS CNC grinding machine was processed,the scatter plot of the distribution function and the scatter plot of the distribution density function of the cooling system were drawn,and parameter estimation and data fitting were utilized to determine that the model of cooling system is exponential distribution. According to the distribution type,the mean time between failures( MTBF) and the maintenance time to repair( MTTR) of the cooling system were calculated,and then the inherent availability( A) of the cooling system could be determined. The results had been fed back to the manufacturer and approved. It is significant to improve the reliability of the CNC grinding machine.
引文
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[13]赵钦志,王立平,王军见.数控机床可靠性试验和评估技术分析研究[J].制造技术与机床,2017(11):17-21.
[14]朱晓翠,许彬彬,王继利,等.基于粗糙模糊规则的数控机床可靠性综合评价[J].工具技术,2015,49(9):14-19.
[2]Kerr D,Pengilley J,Garwood R. Assessment and visualisation of machine tool wear using computer vision[J]. International Journal of Advanced Manufacturing Technology,2006,28(7-8):781-791.
[3]Kuo W. An annotated overview of system-reliability optimization[J].IEEE Transactions on Reliability,2000,49(2):176-187.
[4]申桂香,张英芝,薛玉霞,等.基于熵权法的数控机床可靠性综合评价[J].吉林大学学报:工学版,2009,39(5):1208-1211.
[5]廖雯竹,潘尔顺,奚立峰.基于设备可靠性的动态预防维护策略[J].上海交通大学学报,2009,43(8):1332-1336.
[6]赵宇,杨军,马小兵.可靠性数据分析教程[M].北京:北京航空航天大学出版社,2009.
[7]申桂香,孟书,张英芝,等.平均秩次法在子系统可靠性建模中的应用[J].吉林大学学报:工学版,2014,44(1):101-105.
[8]邹乐强.最小二乘法原理及其简单应用[J].科技信息,2010,23:282-283.
[9]张英芝,申桂香,吴甦,等.随机截尾数控机床三参数威布尔分布模型[J].吉林大学学报:工学版,2009,39(2):378-381.
[10]张世强.曲线回归的拟合优度指标的探讨[J].中国卫生统计,2002,19(1):9-11.
[11]Ronald R Y. A fuzzy measure approach to systems reliability modeling[J]. IEEE Transactions on Fuzzy Systems,2014,22(5):1139-1150.
[12]Yongjun Liu,Jinwei Fan,Yun Li. Reliability modeling and assessment of CNC grinding machine[C]. Quality,Reliability,Risk,Maintenance,and Safety Engineering(QR2MSE),2013,(7):95-98.
[13]赵钦志,王立平,王军见.数控机床可靠性试验和评估技术分析研究[J].制造技术与机床,2017(11):17-21.
[14]朱晓翠,许彬彬,王继利,等.基于粗糙模糊规则的数控机床可靠性综合评价[J].工具技术,2015,49(9):14-19.