![]() In this case, the within-batch variability will include this systematic difference, which will inflate the within-subgroups standard deviation. On the other hand, suppose that within batches a systematic difference exists between the first two parts and the rest of the batch. Since within-subgroups variability is used to calculate the control chart limits, these limits may become unrealistically close to one another, which ultimately generates a large number of false alarms. In this case, the within-subgroup variability is not really representative and underestimates the natural process variability. Since batches are often manufactured at the same time on the same equipment, the variability within batches is often much smaller than the overall variability. ![]() ![]() ![]() When batches aren't a good choice for rational subgroups, control chart limits may become too narrow or too wide. However, this is not always the right approach. For example, when parts are manufactured in batches, as they are in the automotive or in the semiconductor industries.īatches of parts might seem to represent ideal subgroups, or at least a self-evident way to organize subgroups, for Statistical Process Control (SPC) monitoring. In some cases, however, identifying the correct rational subgroup is not easy. Variation within subgroup is therefore used to estimate the natural process standard deviation and to calculate the 3-sigma control chart limits. In a rational subgroup, the variability within a subgroup should encompass common causes, random, short-term variability and represent “normal,” “typical,” natural process variations, whereas differences between subgroups are useful to detect drifts in variability over time (due to “special” or “assignable” causes).
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