基于不同统计模型对压力蒸汽灭菌器故障数据集的可靠性分析OACSTPCD
Analysis on the reliability of failure data set of autoclaves based on different statistical models
目的:基于医院压力蒸汽灭菌器的故障数据,分析评估医疗机构中压力蒸汽灭菌器的可靠性.方法:利用威布尔分布(Weibull分布)、指数分布(Exponential分布)、对数-正态分布(Log-Normal分布)和q-威布尔分布(q-Weibull分布)4种统计模型对压力蒸汽灭菌器的故障数据进行分析,并使用图表工具展示不同分布统计模型在拟合数据时的性能.结果:4种统计模型对比显示,Log-Normal分布统计模型的修正赤池信息准则为564.4512,贝叶斯准则(568.7691)值最低,柯尔莫哥洛夫-斯米尔诺夫(KS)统计量(0.0739)最小,P值最大(P＞0.05),表明分布拟合效果最好,最适合用于分析压力蒸汽灭菌器故障数据集的模型.结论:通过使用不同统计模型对压力蒸汽灭菌器故障数据的可靠性分析,可以为临床工程师优化压力蒸汽灭菌器维护策略提供依据.
Objective:To analyze and assess the reliability of autoclaves of medical institution based on the failure data of the autoclaves of hospital.Methods:The failure data of autoclaves were analyzed by using four statistical models:Weibull distribution,Exponential distribution,Log-Normal distribution,and q-Weibull distribution.Chart tools were used to show the performance of different statistical distribution models in fitting data.Results:Comparisons of 4 kinds of statistical models revealed that the corrected Akaike Information Criterion(AICc)of statistical model of Log-Normal distribution was 564.4512,and the Bayesian Information Criterion(BIC)value(568.7691)of that was the lowest,and KS statistic(0.0739)of that was the smallest(P>0.05).Therefore,fitting effect of statistical model of Log-Normal distribution was the best fit,which was the most suitable model for analyzing the failure data set of autoclaves.Conclusion:Utilizing different statistical models to conduct the reliability analysis for failure data of autoclave can provide references for clinical engineers in optimizing maintenance strategies for autoclave.
钟添萍;张肖宁;郑丽纯
南京大学医学院附属口腔医院 南京市口腔医院医疗设备科 南京 210008
预防医学
压力蒸汽灭菌器可靠性平均无故障工作时间
Pressure steam sterilizerReliabilityMean time between failures
《中国医学装备》 2024 (006)
29-33,39 / 6
江苏省医院协会医院管理创新研究课题面上指导项目(JSYGY-3-2023-344);南京大学医学院附属口腔医院3456骨干人才资助项目(0222M502) Jiangsu Province Hospital Association Hospital Management Innovation Research Topic,General Guidance Project(JSYGY-3-2023-344);"3456"Cultivation Program For Junior Talents of Nanjing Stomatological School,Medical School of Nanjing University(0222M502)
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