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10

Process Capability Analysis for

Non-Normal Data with MINITAB

Timothy Yoap

Process capability analysis is a critical component of the Six Sigma methodology.
Traditionally, process capability was calculated assuming the data are normally dis-
tributed. When the distribution is not normally distributed, it has been widely rec-
ognized that the conventional approach in calculating the capability indices is not
appropriate. Nevertheless few software package provides routines for performing
the analysis. This chapter presents different methods of estimating the process capa-
bility for non-normal data using MINITAB.

10.1 INTRODUCTION

Process capability analysis (PCA) is a critical component of Six Sigma, in both the
operational (DMAIC) and design (DFSS) spheres. In DMAIC, PCA is normally done
during the measure phase to quantify the baseline performance of the process and
during the control phase to validate the improvement. In DFSS, the role of PCA is even
more important. DFSS starts by understanding the customer’s needs and wants. These
are then flowed down to the system and eventually the components level. To ensure
that the product meets the customer’s expectations, each component has to perform at
a certain threshold level. To ascertain whether this has been achieved, PCA is needed
for each component. The capability score -- whether it be z, the number of defects
per million opportunities (DPMO) or C pk -- for each component will be entered into
a management tool called the scorecard. Based on the information in the scorecard, a
decision can be made as to whether the product is good enough to be transferred into
mass production, and if not, resources can be channeled into work on improving those
components that do not meet the capability requirements. Therefore, the accuracy of

Six Sigma: Advanced Tools for Black Belts and Master Black Belts L. C. Tang, T. N. Goh, H. S. Yam and T. Yoap
C 2006 John Wiley & Sons, Ltd
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