If the long-term gap Z.Bench is less than the goal (usually 4.5), then you have to change either the means, the variances, or both, to achieve the goal. This change is made by allocating the gap pools to the elements in the assembly, using Allocate Gap Pools.
Gap mean and variance pools
Indicates how much the mean and variance of the assembly gap must be adjusted to get a Z.Bench of 4.5, using Allocate Gap Pools. If you entered an upper specification on the gap, then Minitab calculates both a mean and a variance pool. If you entered only a lower specification on the gap, there is only one pool to allocate.
Short-term and long-term statistics.
Short-term statistics represent what the assembly would be like if each process were performing perfectly. Because this scenario does not represent reality, Minitab recalculates the statistics, building static shifts or dynamic drifts into the model, and calculates long-term statistics.