Optimize and transform your business today
Challenges, Opportunities and Strategies for Integrating IIoT
Advantage of Enterprise-wide Deployment
TEPCO Group and OSIsoft to Collaborate on IIoT
Pioneers of Digital Transformation
The Rise of Big Data in Utilities
Five ways big data will change the power industry for the better.
Kellogg Reduces Energy Footprint
Learn how Kellogg's uses the PI System to achieve $3.3 million in energy savings.
New Tools for Energy Problems
See how UC Berkeley & Singapore's National Research Foundation use new tools to solve energy problems.
In 2011 when SECURE Energy Services bought the PI System™ for its liquids facilities, the company outlined a roadmap of future applications and target projects for the PI System. The roadmap included everything from creating management dashboards, to training, to process optimization. As part of its most recent roadmap project, SECURE began focusing on heavy equipment optimization in its Processing, Recovery and Disposal division through a pilot project at its landfills. The objective was to improve dozer operations and reduce the cost per ton to process waste.
Over the past several years, biopharmaceutical developer Shire has been working to implement a major overhaul of the way data is handled at their pilot plant in Lexington, Massachusetts. Before implementing the PI System, the company was generating, processing, and storing data in a complicated series of networks and standalone data islands and relying heavily on spreadsheets and manual data entry. One by one, Shire is integrating all of these diverse data sources into a single solution, the PI System. At the OSIsoft's 2016 Users Conference in San Francisco, Paul Turvey and Brad Ebel of Shire, presented how this project has streamlined the flow of information, improved user access to data, reduced errors, and had a substantial impact on the bottom line.
Sinopec Argentina E&P is an oil and gas company in the San Jorge Gulf of Southern Argentina. It has about eight thousand wells in eight areas; in Mendoza, Chubut, and Santa Cruz and a head office in Buenos Aires. In his presentation, Adrián Pavesi, head of the automation team, described the company's first steps with the PI System and their later Enterprise Agreement where the PI System was deployed in all of the company's fields. Two years ago Sinopec began working with OSIsoft and the PI System. The presentation aims to demonstrate two realities. The first is “a mall-scale pilot project that served to leverage the tool (PI System),” and the second is “how we are working with the Enterprise Agreement that we signed, starting with the benefits we were able to obtain from the first deployment,” said Mr. Pavesi.
The PI System gathers data from multiple systems and serves as a universal translator that synchronizes data center operations to boost efficiency, improve planning, and reduce IT and facility costs. With this information data centers can comply with increased government pressure to improve efficiency and reduce environment impact and meet the goals outlined in Executive Orders such as Executive Order 13423 and Executive Order 13514.
The French National Railway Corporation - the Société Nationale des Chemins de Fer Français, or SNCF - is a state-owned company that operates France's world class railway system. SNCF Réseau oversees the management and maintenance of 30,000 kilometers of railway line with 15,000 trains running daily. In 2014, SNCF began a partnership with OSIsoft and now uses the PI System to provide digital tools for workers in the field, enable machine learning, and catch equipment failures before they occur.
Stedin is a gas and electricity distribution system operator with over
four million customers in three of the four biggest cities in the western
part of the Netherlands. As part of its mission, Stedin began to adopt
the IEC 61850 standard. In 2017, OSIsoft built a custom PI Connector
for IEC 61850 to link Stedin's existing PI System to its 61850-compliant
substations. PI System insights showed that tap changers were switching
30 times per day rather than the optimal 16, and allowed the team to
attribute peaks in energy usage to trains accelerating at a nearby station.
With this information, Stedin can now predict when assets may fail to
optimize performance, take preventative action, and reduce outages.