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Master of Science / Industrial & Manufacturing Systems Engineering / Shing I. Chang / The process capability is a measurable property of a process related to the specification of a product. Traditionally, process capability analysis (PCA) measurements are expressed by a process capability ratio (PCR). When using a typical PCR to measure process capability, there are certain assumptions, and critics have been made towards PCR, that some the assumptions are violated. Much research has been conducted to ratify the situations when some of the assumptions are violated. This thesis, is going to demonstrate a research towards process capability using Sample Entropy method. The desirable outcome would be that this method can avoid violating the assumptions.

Firstly, we deal with the verification of normality and other necessary prerequisites needed in this thesis. We also introduce transformations to converse non-normally distributed data to normal and continue with capability analysis. We describe the design of control charts, useful tools to assess process stability. They help us to eliminate assignable causes and leave only chance causes in process. We obtain process in control state. Finally, we introduce both capability and performance ratios for both normal and non-normal data, and analyse some of their properties. At the end of the thesis, we prove acquired knowledge by performing capability analysis of real process.