Hinckley C M
Assured Quality, Manteca, CA 95336, USA.
Clin Chem. 1997 May;43(5):873-9.
Not all of the many approaches to quality control are equally effective. Nonconformities in laboratory testing are caused basically by excessive process variation and mistakes. Statistical quality control can effectively control process variation, but it cannot detect or prevent most mistakes. Because mistakes or blunders are frequently the dominant source of nonconformities, we conclude that statistical quality control by itself is not effective. I explore the 100% inspection methods essential for controlling mistakes. Unlike the inspection techniques that Deming described as ineffective, the new "source" inspection methods can detect mistakes and enable corrections before nonconformities are generated, achieving the highest degree of quality at a fraction of the cost of traditional methods. Key relationships between task complexity and nonconformity rates are also described, along with cultural changes that are essential for implementing the best quality-control practices.
并非所有众多的质量控制方法都同样有效。实验室检测中的不合格基本上是由过度的过程变异和失误造成的。统计质量控制可以有效控制过程变异，但它无法检测或预防大多数失误。由于失误或差错常常是不合格的主要来源，我们得出结论，仅靠统计质量控制是无效的。我探讨了控制失误所必需的100%检验方法。与戴明所描述的无效检验技术不同，新的“源头”检验方法能够在产生不合格品之前检测到失误并进行纠正，以传统方法成本的一小部分实现最高程度的质量。还描述了任务复杂性与不合格率之间的关键关系，以及实施最佳质量控制实践所必需的文化变革。
