Are you a new or seasoned PI System administrator?  Are you interested in knowing some of the best practices for administering the PI Data Archive or the PI AF Server?  Come join this lab and learn about OSIsoft's recommendations on administering and troubleshooting your PI System.  Example topics include best practices for archive management, high availability options for the PI Data Archive and PI AF Server, backup strategies, troubleshooting basics and more.  This lab will benefit the new and seasoned administrators alike.

Power User Lab.

This lab includes use cases to review process condition monitoring vs. machine condition monitoring and the related process reliability vs. equipment reliability. This lab also includes topics related to Reliability Centered Maintenance (RCM), failure modes etc. as they relate to the PI System and AF data models. Additionally, we will cover IIoT’s role in Condition Based Monitoring (CBM).

Discover why PI Vision is truly the next generation of PI System visualization. Create, format and organize your displays with graphics, multi-state values, and trends. Group symbols and create pinned event for comparison purposes. Explore the interaction of AF and PI Vision for events.

This session explores the partnership between Esri’s powerful ArcGIS mapping application and real-time infrastructure offered by the PI System. Discover how easy it is to connect your PI System with your Esri ArcGIS platform to provide critical metrics and spatial awareness to your enterprise. Take advantage of new features within PI Integrator for Esri ArcGIS 2017 to perform both real-time GIS analysis and historical playback of event interactions. This lab will introduce you to leveraging two enterprise systems - OSIsoft PI System (time) and Esri ArcGIS (space) – to achieve product level integration with just a few clicks. We will use the T&D industry as an example to demonstrate how easy it is to bring GIS maps to life by streaming operational data (SCADA, Metering etc) and non-operational data, such as weather, lighting strikes to the control room. The lab exercises highlight how to better manage the grid by enabling one to identify outages, to reduce outage time with more efficient scheduling, and to use historical playback to analyze important events and emergency response. Skills – ArcGIS Operations Dashboard & Web Maps, Asset Framework, and PI Vision

This lab is intended for PI users desiring to learn a new tool for agile, ad hoc, process data analysis.  We will be using Microsoft Power BI to analyze PI Views published by the PI Integrator for Business Analytics.  The hands-on examples help students appreciate of how multidimensional data analysis can help gain command of large datasets through filtering and grouping of process measurements.  The lab will cover other relevant features like how to expand the scope of your analysis be including data from other sources, applying statistical evaluations of your data and by defining measures for benchmarking and advanced analysis.  If you’ve become frustrated trying to manage today’s mega-spreadsheet, this lab might have the answer for you. 

Come to this lab and learn how to get more insight and knowledge from the familiar datasets in your PI System. As a PI System professional you have worked with the PI System and know how it works. Use the concepts in this lab to extract more value and become the super star who creates knowledge from data through good visualization and analytics. Understanding of the basics of PI System tools is a prerequisite for this lab. No prior knowledge of data science concepts are required.

You have already attended several sessions and heard about the power of Asset Framework (AF). You are eager to implement AF or even to expand the existing AF structure in your organization, but… not sure where to start from. Are you wondering if there are any timesaving tips for deploying scalable and consistent AF structures? This is the right lab for you.

This hands-on lab covers scenarios to illustrate the different levels of analytics that are fit-for-purpose when using the PI System. For example, what calculations and analyses do you do in AF? When do you use MATLAB and similar libraries for advanced calculations that hook into AF?  When do you call on “data science and machine learning?” Use cases will include those focused on an equipment, such as a pump, motor or compressor, and those focused on a process. We will also cover examples of advanced analytics that are part of the data collection from the edge devices and contrast these with predictive analytics – both the model development and model deployment (scoring new incoming real-time data) and include cloud vs. fog vs. edge scenarios.