A well-executed project moves from an assessment of the existing OT/IT architecture to an environment that collects data, adds context, and makes it available to users in the form they need for their daily work.
Assessing data sources and user needs
The first stage is to identify the PLCs, SCADA and DCS systems, meters, databases, and other sources that will feed PI System. This includes reviewing the available protocols, data quality, measurement frequency, and historical data requirements.
Use cases are defined in parallel. These may include monitoring plant operations, reporting KPIs, analyzing failures, improving energy efficiency, or making data available to business systems. This establishes from the outset which data actually provides value to users.
Designing the AVEVA PI System architecture and integrations
The assessment provides the basis for the solution architecture. This covers data acquisition, PI Server configuration, communication between OT and IT zones, and system access rules.
This stage also defines requirements for availability, redundancy, backups, time synchronization, and secure communication. Larger environments need to account for multiple plants and integrations with MES, ERP, CMMS, analytics platforms, or a data lake.
The architecture chosen will affect how easily PI System can be expanded later, so it should account for both the current project and anticipated future uses of the data.
Asset Framework adds context to data
Once data acquisition is up and running, the data can be organized. Asset Framework (AF) makes it possible to model the company’s structure—sites, lines, plant systems, and equipment—and associate the relevant measurements with each asset.
This is an important stage of implementation because historical data from thousands of tags can quickly become difficult to use on its own. The AF model allows a process specialist or engineer to analyze a pump, boiler, or production line together with its operating parameters and performance indicators.
This layer can also include Asset Analytics, KPIs, and Event Frames that describe events such as startups, shutdowns, or operating parameters exceeding their limits.
Visualizations, testing, and go-live
Once the data and asset model are ready, user displays are created. AVEVA PI Vision can present current values, trends, events, and KPIs in the context of specific assets and processes.
Before the system goes live in production, testing verifies data acquisition, data quality, calculations, permissions, and system behavior in situations such as a loss of communication. Users also verify that the displays and reports reflect how they actually work.
Testing is followed by go-live, user training, and handover for ongoing support. PI System can then be expanded to include additional data sources, plant systems, analytics, and integrations.
In practice, a phased approach provides the best control over implementation. The organization starts with specific needs, builds a structured data model, validates it in day-to-day work, and only then extends the solution to other areas.
ConnectPoint supports the entire process, from assessment and architecture design through AVEVA PI System integration and configuration to testing, training, ongoing support, and further development of the environment. We describe the scope of our services and the capabilities of AVEVA solutions in detail on our page dedicated to AVEVA solution integration.
