Hi welcome to the first lesson of this course. I would like to start by setting some expectations
for the course. Τhis course is designed for new PI System administrators or seasoned
administrators who are looking for a refresher on the main PI System components. We will not cover
everything that you need to know as a PI System administrator. We highly recommend taking one of
the public courses that we offer for new PI System administrators. The "PI System administration for
IT professionals" and the "Building PI System assets and analytics with PI AF". These are
both four-day courses that will better prepare you for the role of PI System administrator. There's
an appendix section in Chapter 6 of the workbook with some additional troubleshooting tools that
will be useful for administrators. We'll refer to these utilities in the workbook as appropriate.
In this lesson we're going to go over a high-level overview of the PI System. We'll
look at the different components that make up the PI System get a refresher on basic
concepts like PI points in PI time and we'll also talk about the PI System architecture in
this course. The PI System is a collection of software that collects stores and enhances data
from your plant and process and delivers it to users who need it. Simply put the PI System is
everything between the data source and the data consumer. The PI System software components in
this diagram are the PI interface or connector, the PI server and the PI visualization tools.
Interfaces collect real-time data from the data source and send that data to
the data archive for storage. Asset framework is used to organize and enhance the data that
you have stored in the data archive. You can use PI visualization tools such as PI Vision,
PI Processbook and PI Datalink to consume the data and make meaningful analysis with it.
Here we see a more complete picture of our simple PI System architecture. We have a few
data sources sending data to a variety of interfaces. The PI interfaces collect data
from the data sources and send them to the data archive for storage. AF can be used to organize
and enhance that data. It has an analytic speculation engine that can perform real-time
calculations as the data is being received in the data archive from the interfaces. It can also do
backfills using historic data. Event frames are used to help capture important process events
such as down times or tracking parts of the process that are outside acceptable limits.
When those events occur, PI notifications can be used to alert users about them.
Let's get a brief refresher on what a PI point is. A PI point is any data that has
a changing value over time this is collected and stored in the data archive. PI points are
process attributes such as tank level, pump speed, server CPU. The PI System administrator needs to
create a PI point for each of these process attributes. This image shows the PI point
attributes that are used by the interface. PI point attributes such as point source,
location 1 and location 4 information. When this interface starts up it loads
the interfaces with point source of perfmon and interface ID of one and it organizes the
PI points in scan classes based on the location 4 parameter. In this case our
tag has a location 4 of 1 which means that the scan frequency for it is going to be one second.
Okay so let's also get a quick refresher on PI time. So in the PI System we have
fixed time and relative time. Fixed time is a fixed date and time which will never change,
so when you build a report with a fixed time of 23rd of August 2015 at 3 p.m. every time you
open that report the fixed time will never change. However relative time is the date and time that's
relative to the current date and time. This is helpful because you can create dynamic reports,
so when you build a report with a start time with star - 15m and an end time of star this
means that every time you open this report the archive values for the last 15 minutes
will be presented to you. The relative time expression syntax is reference time plus or
minus offset. The reference time tells us when to start and the offset tells us how far back to go.
So star - 15m means star now - to go back in the past 15 minutes. This table shows us some examples
of relative time expressions. So star minus 1h means one hour ago t plus 8h, T plus 8 H means
start from today at midnight and then go forward 8 hours in time, which means 8:00 a.m. today.
Finally, let's go over the PI System architecture in this lab. We have set up
a very simple PI System architecture for this course with one data source, one interface,
one AF server and one data archive collective. A collective is the recommended method for high
availability for data archive to ensure that you always have a backup server in the event
that your primary becomes unavailable. We have setup four virtual machines for this
course. PISRV01 is the machine where the data source and the interface are installed. PISRV01
is the primary data archive collective node. AF and PI vision applications are
also installed on that machine. PISRV02 is the secondary data archive collective node.
PIClient 01 is the client machine where we will be accessing PI System data from.
We'll start using a virtual learning environment in the next lesson.