关于Queuing Analysis的公式

等待时间是服务业流程中计算服务效果的一个重要分析手段，我相信下面修正后的公式增加了到达速度和服务速度的变异系数。然而实际情况是否真的如计算的那么准确，我想肯定是有问题的。不过任何公式都要从实际意义来看，下面的公式至少给出了一种计算等待时间的方法，大多数情形也是可以的。

比如：当你的服务节拍和客户的到达节拍比较一致时，无疑产生的等待时间是巨大的，甚至有时都觉得不可能。

请大家展开自己的看法，不过别让宋祥彦同志看到，不然他再写一本《质疑精益生产》又得吵架了，呵呵！

Queuing theory can be applied by a simple mathematical approximation demonstrated by Kingman which presented that the combinations of following parameters lead to a clear and direct impact on the generation of long queues:
The formula reads:
Time in Queue = { (ca2 + ce2) / 2 } { Util / (1 – Util) } { te }

Utilization(Util)
Utilization = The total amount of demand/total amount of capacity
Generally highly utilization experience longer queues than lightly utilization;

Average Service Times (te)=SAV
As the average service time to a customer expands, the capacity declines and queue time extends;

Variability of Service and Arrivals((ca2 + ce2) / 2 )
Ca is the coefficient of variation of the arrivals = std dev. / average arrival rate
Ce is the coefficient of variation of the service time to each arrival = std dev. / average service time
As variation increases, the mix of variability from both arrivals and service times goes up which tends to produce a longer queue and inconsistent utilization