Seely R J, Munyakazi L, Haury J
Corporate QA, Amgen Inc., Longmont, CO 80503, USA.
Dev Biol (Basel). 2003;113:17-25.
Establishing meaningful and reasonable acceptance criteria for process validation or continual monitoring is crucial to approval and successful manufacturing. The limits should be based on statistical analysis of historical data when possible. The control limits of "mean +/- 3 standard deviations" is one industry standard. However, the limits may be artificially constraining if the standard deviation does not reflect the true variance of the process. Under-estimation of process variance is common with small data sets. This paper presents three methods for correcting underestimated variance, allowing the setting of acceptance criteria that are slightly larger than +/- 3 standard deviations. These limits are more meaningful in that they account for true process variability and will signal process deviations due only to a specific cause.
为工艺验证或持续监测建立有意义且合理的验收标准对于批准和成功生产至关重要。这些限度应尽可能基于历史数据的统计分析。“均值±3 个标准差”的控制限度是一种行业标准。然而，如果标准差不能反映工艺的真实方差，这些限度可能会受到人为限制。对于小数据集，工艺方差的低估很常见。本文提出了三种校正低估方差的方法，从而能够设置略大于±3 个标准差的验收标准。这些限度更有意义，因为它们考虑了真实的工艺变异性，并且只会因特定原因发出工艺偏差信号。
