Abstract

Operator variability is one source of process variation. But how can it be calculated? And how can you effectively identify processes that affect operator variability to drive process improvement? No matter how extensively processes are automated or documented, human factors often influence process performance. For processes that affect operators, it can be challenging to separate the statistically outlying operators to learn from them and drive improvement