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Forensic Schedule Diagnostics to Support Selecting a Methodology in AACE RP29R-03, Forensic Schedule Analysis

机译:法医时间表诊断以支持在AACE RP29R-03,法医时间表分析中选择方法

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This paper discusses the role of performing Forensic Schedule Diagnostics (FSD's) and Criticality Cross-Tabulations (CCT's) for Method Implementation Protocol (MIP) selection, and which includes determination of the likely minimum number of variable or grouped periods necessary should one of the "windows" style methods be selected. The FSD and CCT methods described herein offer a fast and consistent way to assess change across many updates. The nature and degree of change between schedule updates are predictive of relative effort involved with execution of various MIP's. An essential part of assessing this effort is addressed by the fact that these changes are also predictive of the optimal minimum number of variable or grouped periods for efficient execution of windows based MIP's. It identifies where best to divide updates into groups to better understand and present changes to the critical path. This can be accomplished during the first days of an FSA and therefore minimizes lost productivity due to the iterative re-grouping which is often required when such groupings are selected in a fixed, arbitrary, or a trial and error fashion. These methods can be employed independent of specific activity knowledge. Therefore, conclusions can avoid potential bias which sometimes allegedly accompanies subjective selection of variable periods.
机译:本文讨论了在选择方法实施协议(MIP)时执行法医进度诊断(FSD)和临界交叉(CCT)的作用,其中包括确定“ Windows”样式方法。本文所述的FSD和CCT方法提供了一种快速且一致的方法来评估许多更新中的更改。进度表更新之间变化的性质和程度可以预测与执行各种MIP所涉及的相对工作量。评估此工作量的重要部分是通过以下事实解决的:这些更改还可以预测可变或分组时间段的最佳最小数量,以有效执行基于窗口的MIP。它确定了最佳将更新分组的位置,以更好地理解和呈现对关键路径的更改。这可以在FSA的第一天完成,因此可以最大程度地减少因迭代重新分组而导致的生产力损失,而这种重新分组通常是在以固定,任意或反复试验的方式选择分组时进行的。可以独立于特定活动知识来采用这些方法。因此,结论可以避免潜在的偏差,该偏差有时据称伴随可变周期的主观选择。

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