基于AMSAA模型的成型产品可靠性综合评估方法研究
|
摘要
目的改进基于AMSAA模型成形产品的可靠性综合评估方法。方法采用工程界普遍使用的AMSAA模型,利用同类或相似产品研制阶段试验的故障数据,基于综合利用均值和方差信息这一思路,提出一种通过对拟合优度检验统计量的离散系数进行寻优而确定时间环境折合系数的方法。结果通过这一改进方法计算得到置信度为0.9时,产品成形时的MTBF(Mean Time Between Failure)单侧置信下限提高了17%,优于文献结果,且求得置信度分别为0.95和0.99时,产品成形时的MTBF单侧置信下限依然优于文献结果。结论在不同的置信度下,该方法合理可行,符合工程实际。
Objective To improve the reliability evaluation method of molding products based on AMSAA model. Methods A method of determining the time environment conversion coefficient by optimizing the discrete coefficient of goodness of fit test statistics by using the AMSAA model commonly that used by the engineering community was proposed with same or similar product development stage test data based on the comprehensive utilization of mean and variance information. Results The result of this improved method showed that the lower confidence limit of MTBF(mean time between failures) was increased by 17% when the confidence degree was 0.9, which was superior to the result of literature. Moreover, when the confidence level was 0.95 and 0.99, the MTBF confidence level of the product was still better than that of the literature. Conclusion Therefore, at different confidence degree, the method is reasonable and feasible and it is also in line with the engineering practice.
Objective To improve the reliability evaluation method of molding products based on AMSAA model. Methods A method of determining the time environment conversion coefficient by optimizing the discrete coefficient of goodness of fit test statistics by using the AMSAA model commonly that used by the engineering community was proposed with same or similar product development stage test data based on the comprehensive utilization of mean and variance information. Results The result of this improved method showed that the lower confidence limit of MTBF(mean time between failures) was increased by 17% when the confidence degree was 0.9, which was superior to the result of literature. Moreover, when the confidence level was 0.95 and 0.99, the MTBF confidence level of the product was still better than that of the literature. Conclusion Therefore, at different confidence degree, the method is reasonable and feasible and it is also in line with the engineering practice.
引文
[1]BROEMM W J,ELLNER P M,WOODWORTH W J.AMSAA Reliability Growth Guide[J].AMSAA Reliability Growth Guide,2000.
[2]翁雷,廖军,孙国强.电子产品可靠性增长试验综述[J].环境技术,2018(1):20-23.
[3]DAI R,GUO C.Researches and Investigation on Manufacturers′Reliability Test Data of Electronic Parts[J].Energy Procedia,2017,127:242-246.
[4]ZHU X,FANG Z."DGM-AMSAA"Model of Reliability Growth Based on the Small Sample[C]//IEEE International Conference on Grey Systems and Intelligent Services.IEEE,2014.
[5]TALAFUSE T P,POHL E A.Small Sample Reliability Growth Modeling Using a Grey Systems Model[J].Quality Engineering,2017,29(3):455-467.
[6]WAYNE M,MODARRES M.A Bayesian Model for Complex System Reliability Growth Under Arbitrary Corrective Actions[J].IEEE Transactions on Reliability,2015,64(1):206-220.
[7]徐磊,张流圳.可靠性测试的样本量估计[J].电子产品可靠性与环境试验,2018,36(S1):41-43.
[8]黄敏,赵宇.一种产品可靠性综合评估模型的数值分析方法[J].系统工程与电子技术,2002,24(11):131-134.
[9]赵宇,王宇宏.复杂电子设备研制阶段数据的可靠性综合评估[J].系统工程与电子技术,2002,24(1):99-102.
[10]洪东跑,赵宇,马小兵.利用变环境试验数据的可靠性综合评估[J].北京航空航天大学学报,2009,35(9):1152-1155.
[11]ZHANG W,LAN N,SUN P.An Integrated Reliability Evaluation Model of Aircraft Flight Test[C]//International Conference on Reliability,Maintain-ability and Safety.IEEE,2011.
[12]蔡忠义,陈云翔,庄骏,等.基于研制试验数据的可靠性综合评估方法[J].火力与指挥控制,2014(12):70-72.
[13]CAI Z,CHEN Y,ZHANG Z,et al.Method on Integrated Reliability Assessment of Test Data Based on Duane Model[C]//International Conference on Reliability Maintainability and Safety.IEEE,2015.
[14]QIANG L,YUAN X,YANG J.Application of Ant Colony Algorithm in the Optimization of the Time Environmental Conversion Factor of the Reliability Models[C]//2008 International Workshop on Geoscience and Remote Sensing.IEEE,2008.
[15]杜振华,赵宇,黄敏.基于AMSAA模型的研制试验数据可靠性综合评估[J].北京航空航天大学学报,2003,29(8):745-748.
[16]杜振华,赵宇,陈金盾,等.产品设计定型时MTBF置信区间的确定[J].数学的实践与认识,2003,33(2):38-43.
[17]ORTIGUEIRA M D,RIVERO M,TRUJILLO J J.Steadystate Response of Constant Coefficient Discrete-time Differential Systems[J].Journal of King Saud University Science,2016,28(1):29-32.
[2]翁雷,廖军,孙国强.电子产品可靠性增长试验综述[J].环境技术,2018(1):20-23.
[3]DAI R,GUO C.Researches and Investigation on Manufacturers′Reliability Test Data of Electronic Parts[J].Energy Procedia,2017,127:242-246.
[4]ZHU X,FANG Z."DGM-AMSAA"Model of Reliability Growth Based on the Small Sample[C]//IEEE International Conference on Grey Systems and Intelligent Services.IEEE,2014.
[5]TALAFUSE T P,POHL E A.Small Sample Reliability Growth Modeling Using a Grey Systems Model[J].Quality Engineering,2017,29(3):455-467.
[6]WAYNE M,MODARRES M.A Bayesian Model for Complex System Reliability Growth Under Arbitrary Corrective Actions[J].IEEE Transactions on Reliability,2015,64(1):206-220.
[7]徐磊,张流圳.可靠性测试的样本量估计[J].电子产品可靠性与环境试验,2018,36(S1):41-43.
[8]黄敏,赵宇.一种产品可靠性综合评估模型的数值分析方法[J].系统工程与电子技术,2002,24(11):131-134.
[9]赵宇,王宇宏.复杂电子设备研制阶段数据的可靠性综合评估[J].系统工程与电子技术,2002,24(1):99-102.
[10]洪东跑,赵宇,马小兵.利用变环境试验数据的可靠性综合评估[J].北京航空航天大学学报,2009,35(9):1152-1155.
[11]ZHANG W,LAN N,SUN P.An Integrated Reliability Evaluation Model of Aircraft Flight Test[C]//International Conference on Reliability,Maintain-ability and Safety.IEEE,2011.
[12]蔡忠义,陈云翔,庄骏,等.基于研制试验数据的可靠性综合评估方法[J].火力与指挥控制,2014(12):70-72.
[13]CAI Z,CHEN Y,ZHANG Z,et al.Method on Integrated Reliability Assessment of Test Data Based on Duane Model[C]//International Conference on Reliability Maintainability and Safety.IEEE,2015.
[14]QIANG L,YUAN X,YANG J.Application of Ant Colony Algorithm in the Optimization of the Time Environmental Conversion Factor of the Reliability Models[C]//2008 International Workshop on Geoscience and Remote Sensing.IEEE,2008.
[15]杜振华,赵宇,黄敏.基于AMSAA模型的研制试验数据可靠性综合评估[J].北京航空航天大学学报,2003,29(8):745-748.
[16]杜振华,赵宇,陈金盾,等.产品设计定型时MTBF置信区间的确定[J].数学的实践与认识,2003,33(2):38-43.
[17]ORTIGUEIRA M D,RIVERO M,TRUJILLO J J.Steadystate Response of Constant Coefficient Discrete-time Differential Systems[J].Journal of King Saud University Science,2016,28(1):29-32.