What is SPC?

摘要

The arguments for the use of Statistical Process Control (SPC) are many. It is vital that the producer and user alike be able to rely on the efficacy of the process output. In order for SPC to be able to predict quality of the yield there must be a stable population. Once it has been verified that the process is stable and in control, the outcome can be anticipated. If something goes wrong or is about to go wrong, SPC gives clear signals of impending trouble. Walter Shewhart, the creator of SPC, wrote that a process could be said to be in control when, through the use of past experience, we can predict, at least within limits, how the process will behave in the future. Thus, the essence of statistical control is predictability, and the opposite is also true. A process that does not display a reasonable degree of statistical control is unpredictable. In practice, however, the first time that a control chart is used on a process, it is likely to show that the process is out of control. Being out of control does not necessarily mean that the process is not meeting product specifications.