|Abstract Title:||Streamlining the Use of Chemometrics|
|Session Choice:||Development of chemometric methods and data analysis|
|Presenter Name:||Dr Brian Rohrback|
Abstract Information :
Artificial intelligence and machine learning are inevitable results of the work driven by the consumer side of our economy. The question is not whether it will impact refining and chemical plant operation, but how soon and how long it will take for the benefits to outstrip the costs. The goal is to distinguish between vision and hallucination and to provide some practical guidance for making progress in this complicated set of fields. There are three categories of measurements that provide us with the data that will form the basis for any interpretation system: single-purpose sensors, chromatographs, and spectrometers. Multivariate analysis can be used in all three categories and, in fact, is critical to interpreting output from any type of spectrometer. We can easily demonstrate that the use of multivariate analysis for each of the three groupings, even these data sources assembled together, gives faster response, improved flow of information derived from these data, and a significant leg up for process understanding. This information is available and is nearly cost-free.