For those of you that did not have a chance to attend the OSIsoft Academic Symposium on March 20th 2017, you can now view the sessions from the OSIsoft.com web site. Some of the more noteworthy presentations were:
- Panel Discussion: PI System for Data Science Research & Curricula. Several panelists, including Don Paul of USC (ex-Chevron CTO), discussed how industry and academic are using the PI System for collaborative big data analytics and machine learning projects. Also, Lehigh University discussed their Data X program, where real-time data is being used as a component of big data analytics course at Lehigh University. The link is here: http://www.osisoft.com/Presentations/Panel-Discussion--PI-System-for-Data-Science-Research-and-Curricula/
- Pratt Rogers discussed how the University of Utah is including real-time data and the PI System into the metals and mining curriculum. This enables the next generation of engineers to understand how industry leading companies handle their operations and maintenance data. The link is here: Big-Data-and-The-PI-System-–-Teaching-the-Next-Generation-of-Engineers
- Jim Davis of UCLA was our keynote speaker. He shared the vision for his Clean Energy and Smart Manufacturing Innovation Initiative (CESMII). Through use of advanced analytics and modeling, CESMII is helping chemical companies and manufacturers optimize their processing efficiencies. The link is here: Smart-Manufacturing-Innovation-Institute-Joining-Academia-Industry-and-Government-for-Advancement
- A presentation was jointly made by National Instruments (NI) and OSIsoft that described how both companies are working together to provide common solutions. OSIsoft's Dan Lopez followed with a short demo showing how to write PI System data to NI's LabVIEW and how to write NI LabVIEW data into the PI System. This solution is available to OSIsoft university customers at no cost. For the academic community, it was also announced that OSIsoft is developing a hosted, cloud-based PI System that will be used in chemical engineering unit operations labs. The PI System will read and store data from NI equipment, archive the data, and allow students and staff to visualize the real-time and historical data. Students will also be able to download their experiment data for machine learning and analytics using tools such as R, Python, and Matlab. Please contact email@example.com for more specifics.