CPK is not true if data is not normal is PPK true?

Your first statement is incorrect. Cp-Cpk-Pp-Ppk-Z-Sigma all require an approximately normal distribution to be accurate. The difference between the Cp and Pp is simply the type of std dev you are using in your calcuation.

Hi Pete,
This question is very important for me. Can you give us some example data’s ? Because i want to try this point on Minitab.

In reality, you will probably never run accross a perfect bell curve quantity of data.  Therefore, in most all applications, you will be applying bell curves to data that may be near, but does not have a perfect distribution of data to fit a bell curve.  With this in mind, I will direct you to Dr. Donald Wheeler’s book “Introduction to Statistical Process Control” where he points out that slight normallity diviations has very little affect on the predictability of the statistics…even to the extent that the curve may be mis-shaped as badly as a right triangle curve.  Therefore, “you” need to decide how critical your application is and whether you want to apply a bell curve to it.  You may want to use the Chi-square test or the Anderson-Darling “p” to help you decide.  Of course, any good stats software package today will also calculate the proper CpK for you if you tell it to use curve fitting (a non-normal curve) to do the calculations.