OSISoft PI best practices suggest that PI tags conform to a strict naming convention to allow users to quickly find their data within a small PI database today and a larger database in the future. One needs to consider how to efficiently differentiate and search a large number of PI tags that could span multiple units, areas, buildings, and locations, as well as consider the diversity of user's backgrounds that access PI.
Knowing the what to consider can make it easy to design a good PI Tag naming convention and adhering to the convention can make it easy for your users to efficiently find the data they need.
Introduction
The OSISoft PI system records data over time in a time-series database so you can trend and analyze historical data within a timeframe (ex. Power consumption over the last 24 hrs, valve positions during the last production).
One database can store a complete history of all devices and inputs within a facility (CPU utilization, Memory and disk space consumption, network throughput, CPU fan speeds, CPU temperature, cabinet air flow, power consumption, etc). The OSISoft architecture can handle millions of different datapoints recorded at subsecond intervals (ex. 10,000 values/sec).
Each different datapoint is known as a PI tag. A PI tag holds a single value over time (ex. a flowrate, a valve position). If an instrument emits multiple attributes (ex. process value, setpoint, alarm state, upper limit), each of these attributes would be stored in its own PI tag.
Criteria
Tag names must be able to differentiate:
Locations
Units and areas
Data types within one instrument (ex. setpoint vs. process value)
Audiences
To handle each of these cases, Automated Results recommend a PI Tag be made up of different segments and that each segment be separated by a unique character. For example:
Facility:Unit_EquipmentName.DataType
Example: Boston:UF01_InletPressure.SP
Boston facility
Ultrafiltration unit 1
Inlet Pressure sensor
Setpoint value
Differentiate Equipment
One might use PI to capture historical information for one processing unit (100 PI tags) or all processing units within a large global corporation (1,000,000+ tags). As the number of PI tags grows, it can become difficult to find the right data when you need it, even if you are familiar with the facility and the PI data.
To handle needs today and into the future, create a tag name in segments that represents an equipment hierarchy from physical locations, building, processing areas, and units (Note: The ISA S88 Batch standard is a good reference for equipment naming.).
Differentiate Equipment Types
Within a given unit, there can be a large number of tags and finding a specific data point can be confusing. If you pre-define a set of acronyms to that represent each type of equipment, one can quickly isolate the set of tags.
For example:
VLV Valve
FLO Flowrate
LVL Level
TMP Temperature
Differentiate Data Types
A given a single piece of equipment, there can be a set of data types assigned to it. Similar to equipment acronyms, establish a pre-defined set of data types.
For example:
CO Control Output
PV Process Value
SP Setpoint
Diverse Audiences
As your PI implementation evolves, you will find a broader audience interested in accessing PI data from line operators to upper management, vendors, and possibly customers.
One could use the facility drawings and its naming conventions to define your PI tag names, but you may be missing one or more segments of your user base; those users who are not engineers and/or are not close enough to the process to relate to the names.
There are 3 ways to address a diverse audience:
Replace engineering naming with more generic abbreviated text
Include additional abbreviated text in the tag name
Define a standard PI tag description naming convention
Extending the tag name to include a larger audience can introduce tag names that are too long and take up too much 'real estate' on the screen, especially the legend of a trend.
A PI tag description naming convention is a great idea and should be done, but have users not familiar with the process have to rely on the additional description field to find their data is adding a level of training and support complexity.
We recommend the first method to handle a wide audience by using a more universal set of abbreviations in order to keep the tag name short and simplify the PI Tag search techniques.
Summary
Even if you have a small PI system, pre-define a segmented PI Tag name that considers the long-term use of the PI within your company and a broad audience.
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