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A Rationale for Lean Models for Quantitative Schedule Risk Analyses

机译:用于定量时间表风险分析的精益模型的理由

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The reliability of quantitative schedule risk analyses (QSRA) outcomes is dependent upon using robust risk models. These models must fairly represent the project plan, be simple to follow, contain a level of detail where duration uncertainties and risks can be meaningfully assigned, and be feasible to infer from historical data. This paper expands arguments in support of fit for purpose summary schedules as an appropriate type of QSRA risk model for large EPC projects. To that end, it discusses issues associated with the stability of Critical Path Method (CPM) networks. Using examples from actual projects, it explores how those issues curtail the usability of detailed schedules CPM networks as risk models, and precludes the use of historical data as a source of risk estimates evaluation. Then it explains how lean, fit for purpose summary risk models, can be designed for improving CPM network stability and can make historical data inferences more feasible to use, thus increasing the predictability of QSRA outcomes.
机译:定量时间表风险分析(QSRA)结果的可靠性取决于使用稳健的风险模型。这些模型必须相当代表项目计划,简单遵循,包含一个细节水平,其中可以有意义地分配持续时间不确定性和风险,并且可以从历史数据推断出来。本文扩展了支持适合于目的摘要计划的参数作为大型EPC项目的适当类型的QSRA风险模型。为此,它讨论了与关键路径方法(CPM)网络的稳定性相关的问题。使用实际项目中的示例,探讨这些问题如何将详细的时间表CPM网络作为风险模型的可用性缩短,并排除使用历史数据作为风险估计评估的来源。然后,它解释了如何精益,适合目的摘要风险模型,可以设计用于提高CPM网络稳定性,可以使历史数据推断更加可行,从而提高了QSRA结果的可预测性。

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