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Year: 2017

With the high-fidelity insights from the PI System, WHUD pinpointed a leak spilling nearly 147 million gallons a year, reduced its costs by over $1 million and postponed $15 to $20 million in upgrades.

RWTH Aachen University, located in Germany, is one of the largest technical universities in Europe. Founded in 2014, the university’s PEM (Production Engineering of E-Mobility Components) institute focuses on designing electric mobility solutions. To make electric vehicles more affordable for mass production, engine batteries must be produced in a cost-effective manner. With the help of the OSIsoft PI System, PEM Aachen used operational data to optimize the production process in order to: predict battery quality during production in order to eliminate the cost and time associated with end of line testing, reduce overall production cost by as much as 20%, and shrink batter scrap rates from 10% to 2%.

The industry is all a buzz with the idea of 'machine learning' and 'analytics' - these are the latest shiny objects everyone is talking about and trying to bring value to their organization with. But, there is also a lot of confusion on what these terms mean, and more importantly, how and where to implement them for success.This webinar aims to demystify these concepts and demonstrate how you can leverage them with PI System data.
Year: 2017

Digital Water: How One Community Saved More Than $20 Million By Finding Leaks With Data Tennessee’s White House Utility District saw employee productivity go up, expenses go down and a major capital expansion go away. Power & Utilities 2017-12-08 SAND LEANDRO, CA (December 6, 2017) -- White House Ut ...