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Regional Seminar Series Philadelphia. “PI Baking” Contest. Pete Long PI Administrator Glatfelter, Spring Grove, PA. October 13, 2009. 1863 - First Paper Machine. Today’s Paper Machines. Spring Grove Architecture…. …Client stations - ProfileView - SQC
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Regional Seminar Series Philadelphia “PI Baking” Contest Pete Long PI Administrator Glatfelter, Spring Grove, PA October 13, 2009
Spring Grove Architecture… …Client stations - ProfileView - SQC - DevNet Utilities Spring Grove… - ProcessBook - Datalink - Control Monitor PI Servers • Analytical tools • - Performance Eq. • - Control Monitor • - email Notifications • Other systems • - ERP • - Maintenance • - LIMS • - CEMS Interface node Interface node Data Source (DCS, PLC, etc) Data Source (DCS, PLC, etc)
Glatfelter: Everyone Benefits when everyone is involved. Pulp and Paper • “Simply put, the more people that contribute to our PI system, the better the intelligence we get from it. The different perspectives allow us to collectively mine more information from the data.” • Steve Groetz, Process Automation Manager. Customer Business Challenge Solution Customer Results / Benefits • ProcessBook & DataLink projects were received from 6sigma black belts, lab techs, and process engineers. • Projects were essential to prove a business case, provide real-time process information, and compare current runs to QC standards. • On project continues to verify and maintain quarterly savings of over $100k. • Create an initiative to generate individual motivation beyond the engineering department to the entire workforce exploiting PI data with goals of improving visibility, reducing time, increasing quality, and reducing costs. • Finite engineering workforce exercising a broad range of disciplines. • Limited capitol resources: “making do with what we have” • Wealth of mill wide process data in PI not being effectively interrogated.
Contest example… “Value Now” Problem: Inability to trend Control Monitor stats in ProcessBook Solution: Extract data from CM database into Excel and filter, sort, trend and report in Excel Result: Improved visibility of loop performance data
Contest example… “Value Now” Problem: QC and Mfg wanted to compare real time scanner data against lab test results as soon as possible Solution: Use ODBC data sets in ProcessBook to access MES system and display lab data and control limits against real time measurements Result: Ability to make control decisions and correct problems in real time. Minimize waste and rework Real Time MES Data Real Time PI Data Averaged PI Data
Contest example… “Value Now” Problem: Many grade variations with variable property setpoints hard to document and display Solution: Collect actual properties per run and display so operator can easily compare current to previous runs Result: Visualization of data from prior runs enables operators to quickly and easily see if they are on track for the specific grade and make adjustments in real time.
Wrap-up… “Value Now, Value over Time” Save Money Save Time Improve Visibility Increase Production Reduce Downtime
Glatfelter: Everyone Benefits when everyone is involved. Pulp and Paper • “Simply put, the more people that contribute to our PI system, the better the intelligence we get from it. The different perspectives allow us to collectively mine more information from the data.” • Steve Groetz, Process Automation Manager. Customer Business Challenge Solution Customer Results / Benefits • ProcessBook & DataLink projects were received from 6sigma black belts, lab techs, and process engineers. • Projects were essential to prove a business case, provide real-time process information, and compare current runs to QC standards. • On project continues to verify and maintain quarterly savings of over $100k. • Create an initiative to generate individual motivation beyond the engineering department to the entire workforce exploiting PI data with goals of improving visibility, reducing time, increasing quality, and reducing costs. • Finite engineering workforce exercising a broad range of disciplines. • Limited capitol resources: “making do with what we have” • Wealth of mill wide process data in PI not being effectively interrogated.