de Vries A, Conlin B J
Department of Animal Science, University of Minnesota, Saint Paul 55108, USA.
J Dairy Sci. 2003 Jun;86(6):1970-84. doi: 10.3168/jds.S0022-0302(03)73785-0.
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 approximately 300 d (100 cows) or 60 d (1000 cows) with the cusum charts. For a change to 0.35 EDE, observed ATS were approximately 50 d (100 cows) and approximately 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.
用于监控生产过程的统计过程控制（SPC）图表在奶牛管理中尚未得到广泛应用。休哈特控制图和累积和（cusum）控制图旨在确定奶牛正常发情检测效率（EDE）变化中的真实变化。使用随机模拟模型来跟踪100头和1000头牛群中个体奶牛随时间的表现。发情检测率（EDR），即观察到的发情次数除以估计的发情天数（1至60天期间），用于监测EDE。针对两种牛群规模，基于正态分布和二项分布设计了EDR控制图，设定EDE为0.65；然后将EDE设定为0.65（无变化）、0.55、0.45或0.35，并在400次运行中确定首次检测信号的平均天数（ATS）。在0.65 EDE时观察到的ATS可能与目标ATS不同，这取决于SPC图表设计以及授精奶牛发情天数的估计比例。对于EDE的较大变化以及1000头牛的牛群，观察到的ATS较短。使用cusum控制图时，对于EDE降至0.55的变化，观察到的ATS约为300天（100头牛）或60天（1000头牛）。对于EDE降至0.35的变化，观察到的ATS约为50天（100头牛）和约11天（1000头牛）。休哈特控制图的表现类似，或根据周期长度发出变化信号的时间更长。当在设计中使用非最优参考值时，cusum控制图上观察到的ATS比最小值长得多。当SPC图表设计的目标ATS较长且EDE变化较小时，观察到的ATS也较长。基于正态分布和二项分布的控制图总体表现相似。统计过程控制图能够足够及时地检测出发情检测效率的变化，在奶牛管理中可能具有潜在用途。
