What I wanna stress again is that capability ratio is not everything， there are too many misuses in the industry， don‘t count all on it.
我想再一次强调的是加工能力比率并不是万能的，在工业上有很多的误用，不要全部依靠它来计算。
Here is my answer to the question of 32 sample size：
这里是我对样本尺寸为32的问题的回答。
A practice that is increasingly common in industry is to require a supplier to demonstrate process capability as part of the contractual agreement. Thus， it is frequently necessary to prove that the process capability ratio Cp meets or exceeds some particular target value——say， Cp0. This problem may be formulated as a hypothesis testing problem：
一个要在工业中日渐成熟的练习是需要一个供应者示范如契约的协议部份般的程序能力。 因此，有必要经常证明加工能力比率CP等于或者超过如CP0的一些特殊目标价值。这个问题可能被制定为一个假设的测试问题：H0：Cp= Cp0 (or the process is not capable)
H1： Cp≥ Cp0 (or the process is capable)
We would like to reject H0 (recall that in statistical hypothesis testing rejection of Null hypothesis is always a strong conclusion)，thereby demonstrating that the process is capable. We can formulate the statistical test in terms of Cp‘，so that we will reject H0 if Cp’ exceeds a critical value C.
我们想要否定H0( 取消对统计的假设中无效力假设的测试否定一直是一个强大的结论)。因此，示范加工是有能力的。我们可以根据 Cp‘ 制定统计的测试， 所以如果 Cp’超过一个关键的价值 C，那么我们会否定H0 .
Kane(1986) has investigated this test， and provide a table of sample sizes and critical values for C to assist in testing process capability. We may define Cp(High) as a process capability that we would like to accept with probability (1-α) and Cp(low) as a process capability that we‘d like to reject with probability (1-β)。 Please refer to the table created by Kane and used by American Society for Quality Control.
凯恩 (1986) 已经调查这上述测试， 而且向C提供一张有样品大小和关键值的表给来协助测试的加工能力。就如我们喜欢接受(1-α)的可能性和CP(低)作为程序能力和否定(1-β)的可能性一样，我们可以将CP(高)定义为一个加工能力。请查阅凯恩所创建的并为美国社会质量控制所用的表格.考试通
来源:考试网-质量工程师考试
