Jarita Sirois

Newest posts in each industry group - check them all out!

Blog Post created by Jarita Sirois on Oct 4, 2016

Here are the links to each group and a couple of new threads for you to see if you want to join!

Let us know if you have any questions!



Academic Users Group

Have You Thought About PI For Tracking Your Stadium Activity?

As universities continue to reduce energy consumption on their campus facilities, buildings are getting "smarter", due to the deployment of IoT (Internet of Things) power consumption sensors and improved analytics using meter and building automation system (BAS) data.  That's good for everyone. In the past few years, the PI System has also been used to monitor energy usage at Major League Baseball stadiums and ice quality at NHL hockey arenas.  Here's just a few of the use cases:


Recent article on smarter stadiums:  How the smart stadium will transform the smart city

Short video on MLB's San Diego Padres vision for monitoring Petco Park:  OSIsoft: San Diego Padres & SDG&E: A Community System Story - YouTube

Short video about the NHL's Minnesota Wild and their journey to improve playing ice quality: The Minnesota Wild on Better Data, Better Communication, Better Ice - YouTube

Facilities and Energy Management

Facilities and Energy Management Example Template


These PI AF Example XMLs/Templates are meant to provide you with an idea of how you could use PI AF in your PI System to monitor important conditions within your facilities with regards to energy management. We hope that you will use the XMLs as a starting point for building out your own hierarchies and implementing your own analyses.

Download the kit here!


Improving Performance with Integrated Smart Buildings

This white paper examines:

  • What makes a smart building
  • Smart-building strategies being used by specific buildings
  • Benefits of integration
  • How existing buildings are using integration to become smarter
  • Challenges to creating smart building

Mines, Metals, Metallurgy & Materials

2016 XXVII IMPC Asset and Energy Optimization in the Cloud

It presents that the latest use of ASSET Framework and Event Frames with the synergy of using BI Self Services tools.

The operational intelligence embedded in PI Analytics enables to evaluate the performance of a processing plant.

A customer calls this strategy Follow the Money.


Another IROC for BHP Billiton

Following the Pilbara Iron Ore IROC, the BHP coal business has just opened a centralized monitoring and control room in Brisbane, increasing focus on real time data & operational decision support

BHP launch coal remote operations centre - Australian Mining

I'm interested in any news of other mining companies investing in this trend?

Oil and Gas - Midstream

2016 O and G Petchem City Seminar Series Midstream Final

This is a Midstream Deck used in the O&G City tour and contains some excellent use cases and Midstream overview. You can view or download the powerpoint.

Life sciences, Pharma, Spec Chem

Industry Specific Reference Architecture

This paper describes an enterprise-level architecture for the PI System in the Life Sciences industries.


AF Example Template for Life Sciences

I want to share with the Life Sciences Group a PI AF example that we use internally for demos. It is just an example of how a starting hierarchy might look like, it is not completed and still a work-in-progress. If you would like to make any improvements to the template, hierarchy, etc. – We encourage you to share your improvements and ideas by just adding a comment to the post.


Download the kit here!

Power Generation

How to get PJM real-time / forecasting electricity rate to PI?

We will be operating thermal storage tank for a chiller plant located at Bethesda, Maryland. We would like to download the real-time and forecasting electricity rate from PJM - Home  website and save them in the future PI tag. This will help us to decide the operational strategy.

Performance Optimization in Power Generation - White Paper

This document is intended to be a comprehensive guide to calculate the heat-rate and other controllable loss parameters for a fossil steam generating unit. Most of the pertinent calculations are explained and presented in a form where they can be implemented using PI Asset Analytics. Some useful industry rule-of-thumb guidelines are applied in calculations to quickly determine the heat-rate effects of various deviations. However, note that particular heat-rate effect calculations can vary by unit design and should be performed using the parameters in the thermal performance kit provided by the turbine manufacturer for a particular plant to be most accurate.

Pulp & Paper


This OSIsoft AF example spreadsheet will assist in your building of an AF mill-wide model. The goal is to have you answer questions about your mill assets and from your answers, an AF structure will be created. We have included some “typical” PI Point suggestions for most of the equipment types found in a P&P mill. Once the AF structure is created on your AF System, you can then map the suggested points to PI tags you might have in your system.

Transmission and Distribution

Transmission and Distribution User Group 2016 Conference Presentations

The T&D Users Group met on Sept 14-16, 2016 in Scottsdale, AZ for two days of great talks and presentations. You can see all the presentations here, including:

ERCOT Promotion of AF Systems for Weekly Database Loads

Unlocking Grid Analytics using PI AF, Maps and Rosetta Stones

How TEP leverages PI to monitor its distribution system

Condition Based Maintenance with PI AF working session

Transportation and Supply Chain

Mobile Asset Performance Monitoring Example Kit

In this example kit, haul trucks, used in mining and other industries, are monitored for standard performance metrics, such as location, fuel consumption, tire pressure, and engine status. For more details on how PI AF is used for truck monitoring, see the video on PI Square: Introduction to the Asset Based PI Example Kit - Mobile Asset Performance Monitoring.

Supply Chain Optimization at Arcelormittal Mines Canada

A data-driven logistics strategy helps ArcelorMittal Meet increased Production Targets. "We need to bridge the gap between operations and business systems. [When] an operator on the shop floor actually knows how he's contributing to the bottom line, pretty amazing things begin to happen."

Water and Wastewater

Big Data and Machine Learning in Water Industry

How does your company handle Big Data and Forecasting currently?

Would you be interested in participating in a Data Science initiative, involving PI and Machine Learning in order to forecast Water Demand, Reduce Leakage, optimize your Energy Management etc ?

Let us know your thoughts!


Leak or burst detection solutions

I was wondering if there are any leak or burst detection solutions out there built on PI.

Currently building our own set with things like, increasing trend minimum daily flow, mass balance on DMA's, etc.