Attending the AIChE Spring Meeting 2015 in Austin, Texas? ProSensus will be exhibiting our desktop multivariate data analysis solution ProMV, and our online solution for real-time batch monitoring (ProBatch Online) and control (ProBatch Control).
ProSensus will be demonstrating how to find the root cause of product variation, predict product quality, and find optimal operating conditions using our solutions for both batch and continuous processes. Stop by booth 118 for a quick demo and for some free swag. If you’re there only for free swag that’s okay too.
In addition to exhibiting at the AIChE spring meeting, ProSensus founder and CEO Dr. John F. MacGregor will be giving two talks during the first ever Big Data Analytics session. John’s first talk will focus on how you can use the vast amounts of data you are already collecting to improve product quality, increase yield, and reduce operating costs.
John will then discuss how to implement multivariate data analysis to troubleshoot your process in real-time using live data. Interested in attending both, or one of John’s talks? Read on for time, location and full abstracts.
Abstracts
Learning from Historical Data: A key to process improvement and optimization
Tuesday, April 28, 2015: 11:15 AM | 12B (Austin Convention Center)
Process and laboratory computers collect large amounts of data. Knowing how to extract actionable information from these data is crucial. This seminar will look at recent advances and applications in the industrial use of multivariate data analysis methods for process improvement and optimization.
A brief conceptual introduction will be given to the latent variable / chemometric modeling methods used and why they are so much more suitable for the analysis of historical process data than traditional statistical methods.
Industrial examples will include the identification of important process and raw material variable effects on final quality in a continuous process, and troubleshooting and optimizing a batch specialty chemical process.
Using Production and Image Data for Real-time Improvement of Process Operations
Tuesday, April 28, 2015: 3:30 PM | 12B (Austin Convention Center)
DCS and PLC systems collect large amounts of data routinely every few seconds. More complex PAT and image based sensors are also in more common use. Knowing what these data are telling you about your process so that the process operations can be improved, and so that operators or control systems can respond in real-time is critical to improved plant performance.
This presentation looks at recent advances and applications in the industrial use of on-line multivariate data analysis systems for process improvement, monitoring and control. These include:
- Real-time monitoring of batch specialty chemical processes.
- Predictive control of final product quality in batch processes using multivariate data based models and mid-course corrections.
- Real-time inspection of multiple defects on synthetic rubber bales via advanced multivariate image analysis and relating the defect severity results to upstream processing conditions to significantly improve the process.
Hope to see you at the AIChE Spring Meeting 2015.
