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Design and Performance of Statistical Process Control Charts Applied to Estrous Detection Efficiency

机译:用于发情检测效率的统计过程控制图的设计和性能

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Statistical process control (SPC) charts to monitor production processes have not been widely used in dairy management. Shewhart and cumulative sum (cusum) control charts were designed to determine true changes in estrous detection efficiency (EDE) amidst normal variation in dairy cattle. A stochastic simulation model was used to track performance over time of individual cows in herds of 100 and 1000 cows. Estrous detection ratios (EDR), calculated as observed estruses divided by estimated estrous days (in periods of 1 to 60 d), were used to monitor EDE. Control charts for EDR, using normal and binomial distributions, were designed at 0.65 EDE for both herd sizes; then EDE was set to 0.65 (no change), 0.55, 0.45, or 0.35 and average days to the first detection signal (ATS) in 400 runs was determined. Observed ATS at 0.65 EDE could differ from the target ATS, depending on the SPC chart design and estimated proportions of estrous days for inseminated cows. Observed ATS were shorter for larger changes in EDE and for the 1000-cow herd. Observed ATS for a change to 0.55 EDE were ~ 300 d (100 cows) or 60 d (1000 cows) with the cusum charts. For a change to 0.35 EDE, observed ATS were ~ 50 d (100 cows) and ~ 11 d (1000 cows). Shewhart charts performed similarly or took longer to signal changes depending on period length. Observed ATS on cusum charts were much longer than minimum when non-optimal reference values were used in the design. Observed ATS were also longer when SPC charts were designed with a longer target ATS and change in EDE was small. Control charts using normal and binomial distributions generally performed similarly. Statistical process control charts detected changes in estrous detection efficiency soon enough to be potentially useful in dairy management.
机译:用于监控生产过程的统计过程控制(SPC)图表尚未在乳制品管理中广泛使用。设计Shewhart控制图和累积总和(cusum)控制图来确定奶牛正常变异情况下发情检测效率(EDE)的真实变化。随机模拟模型用于追踪100头和1000头母牛群中每头母牛随时间的表现。发情检测率(EDR)是通过观察到的发情除以估计的发情天数(1至60 d)计算得出的,以监测EDE。使用正态分布和二项分布的EDR控制图针对两种畜群大小设计为0.65 EDE。然后将EDE设置为0.65(无变化),0.55、0.45或0.35,并确定400次运行中距第一个检测信号(ATS)的平均天数。 EDE为0.65时观察到的ATS可能与目标ATS不同,这取决于SPC图表设计和受精母牛发情天的估计比例。对于较大的EDE变化和1000牛群,可观察到的ATS较短。观察到的ATS改变为0.55 EDE时,根据曲线图可以看到300 d(100头母牛)或60 d(1000头母牛)。如果将EDE更改为0.35,则观察到的ATS分别为〜50 d(100头母牛)和〜11 d(1000头母牛)。 Shewhart图表的表现类似,也可能需要更长的时间才能根据周期长度发出变化信号。当在设计中使用非最佳参考值时,在客户图表上观察到的ATS远远大于最小值。当将SPC图表设计为具有更长的目标ATS且EDE的变化很小时,可观察到的ATS也更长。使用正态分布和二项分布的控制图通常执行类似的操作。统计过程控制图能够尽快检测到发情检测效率的变化,足以在乳品管理中发挥作用。

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