Monte Carlo simulation using Excel(R) spreadsheet for predicting reliability of a complex system

S. G. Gedam, S. Beaudet
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引用次数: 35

Abstract

A technique for performing Monte-Carlo simulation using an Excel spreadsheet has been developed. This technique utilizes the powerful mathematical and statistical capabilities of Excel. The functional reliability block diagram (RBD) of the system under investigation is first transformed into a table in an Excel spreadsheet. Each cell within the table corresponds to a specific block in the RBD. Formulae for failure times entered into these cells are in accordance with the failure time distribution of the corresponding block and can follow exponential, normal, lognormal or Weibull distribution. The Excel pseudo random number generator is used to simulate failure times of individual units or modules in the system. Logical expressions are then used to determine system success or failure. Excel's macro feature enables repetition of the scenario thousands of times while automatically recording the failure data. Excel's graphical capabilities are later used for plotting the failure probability density function (PDF) and cumulative distribution function (CDF) of the overall system. The paper discusses the results obtainable from this method such as reliability estimate, mean and variance of failures and confidence intervals. Simulation time is dependent on the complexity of the system, computer speed, and the accuracy desired, and may range from a few minutes to a few hours.
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利用Excel(R)电子表格进行蒙特卡罗模拟,预测复杂系统的可靠性
开发了一种使用Excel电子表格进行蒙特卡罗模拟的技术。这种技术利用了Excel强大的数学和统计功能。首先将所研究系统的功能可靠性框图(RBD)转换为Excel电子表格中的表格。表中的每个单元格对应于RBD中的特定块。这些单元格中输入的失效次数公式符合相应块的失效时间分布,可以遵循指数分布、正态分布、对数正态分布或威布尔分布。Excel伪随机数生成器用于模拟系统中单个单元或模块的故障次数。然后使用逻辑表达式来确定系统的成功或失败。Excel的宏功能可以在自动记录故障数据的同时重复该场景数千次。Excel的图形功能随后用于绘制整个系统的失效概率密度函数(PDF)和累积分布函数(CDF)。讨论了该方法的可靠性估计、故障的均值和方差以及置信区间等结果。仿真时间取决于系统的复杂程度、计算机速度和所需的精度,从几分钟到几个小时不等。
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