(54i) Determining Product Specification for Count Data
AIChE Spring Meeting and Global Congress on Process Safety
2017 Spring Meeting and 13th Global Congress on Process Safety
Spring Meeting Poster Session and Networking Reception
Big Data Analytics Poster
Monday, March 27, 2017 - 5:00pm to 7:00pm
In order to ensure that a business can produce minimum amount of out of specification product, it is critical to include the statistical knowledge of its process and measurement capability in determining the product specification. This can be done by following âBig Dataâ concepts, utilizing historical process and/or lab data. As a standard six-sigma methodology, the capability of measurement is commonly evaluated from P/T ratios. However, the evaluation of P/T ignores within-product variation, and is inadequate for non-normal data distributions and/or concentration-dependent standard deviations. We propose a more generally applicable approach, in which we focus on confidence levels (or âcritical fallout valuesâ) rather than on P/T ratios. Our approach allows for product variation and for all possible data distributions, including discrete distributions.
At The Dow Chemical Company, we have started to apply our generalized approach to the evaluation of method capability in the case of Poisson-distributed data. We will illustrate the merits of our approach from our experiences in this specific application.