Join us at the Conference on Statistical Practice (CSP) 2017, February 23rd – 25th, in Jacksonville, Florida. CSP provides participants with opportunities to learn new statistical methodologies and best practices to solve real world problems. ProSensus founder, Dr. John MacGregor will be presenting a talk on how multivariate data analysis can be used to optimize processes and products using historical data.
The huge volume of historical (“BIG data”) being collected routinely by process industries is happenstance data characterized by extreme correlation among the variables. This results in a lack of regression model uniqueness and a lack of causal information among the variables. The unfortunate result is that this vast amount of readily available historical data is often not used to optimize processes or products. Dr. John MacGregor will illustrate how multivariate analysis can determine causal relationships using historical data, allowing one to optimize process or products. This will be illustrated using several industrial problems and data sets, including:
- Optimization of batch and continuous chemical processes (a herbicide and a polymerization process, respectively).
- The development of new and improved products through the simultaneous selection of raw materials, formulation ratios and process conditions (e.g., functional polymers for golf ball cores, high performance polymeric coatings, and food formulations).
Join us Saturday, February 25th, 11:00 AM – 12:30 PM in the City Terrace 7 room to hear John’s talk (complete abstract can be found here).
Not attending CSP 2017? Contact us to learn more about how multivariate data analysis can be used to optimize your process or products.