In the age of IoT, effective data management, including accessibility, is critical. The proliferation of connected sensors generates a massive volume of timestamped data that needs to be shared, centralized, and analyzed. This three-part blog series reviews the value of collaborating on time series data and the challenges associated with it. Specifically, it explores the capabilities and limitations of PI System, a popular data historian used throughout manufacturing, and illustrates how TDengine can be used to extend this system to enable effective data centralizing and sharing.
Blog: Supercharging PI System for Data Sharing & Advanced Analytics: Part One
Blog: Supercharging PI System for Data Sharing & Advanced Analytics: Part Two
For more on extending PI System’s capabilities for data sharing and advanced analytics, download the full whitepaper.
A New Approach: TDengine for PI System
TDengine has built a powerful hybrid solution that extends PI System to enable seamless data sharing and centralization, making it easy for businesses to break down data silos and generate actionable insights.
Benefits:
- Rapid and simple implementation: It can be installed, configured, and start streaming data in under an hour, ensuring a quick return on investment.
- No rip and replace: It’s built to centralize PI System data without replacing the entire system. Data is streamed to TDengine and can be viewed and processed natively back within PI AF.
- Operating at serious scale: TDengine’s time series database is proven to perform successfully on one billion IoT devices. TDengine for PI System can easily scale by using multiple connectors and has been tested on hundreds of thousands of PI points for a single connector.
- Seamless data sharing: Once the data is centralized, users can leverage the powerful data-sharing capabilities of TDengine.
Replicating Data
TDengine for PI System allows users to quickly replicate data to the cloud, reducing deployment time from months to minutes. Users have the option of streaming data continuously from PI points or AF templates to TDengine Cloud. After a quick setup, the integration handles the messy business of extract, transform, and load, and enables automatic backfill after any disruptions.
- Replicating from AF: Users just select a template, and TDengine for PI System will start streaming all relevant data.
- Replicating PI points: For those who aren’t using AF, a convenient point builder tool allows users to stream individual PI points to the cloud.
PI System Integration
The TDengine for PI System uses the AF SDK to query historical data from the PI Data Archive, set up PI and AF data pipes for streaming data, and connect to PI AF to query the AF structure. It also creates the corresponding tables and writes this data over a secure RESTful API to TDengine Cloud.
The TDengine Data Reference is an AF Custom Data Reference that queries data within TDengine and allows users to interact with TDengine as though it were a PI Point within the PI Data Archive. In this way, TDengine data can be used alongside PI data in PI Vision.
Case Study: Data Centralization & Sharing for Electric Utilities
Improving a power generator’s financial, operational or environmental outlook requires insights that can only be developed with a full view of the system’s operations. TDengine partnered with a management consultant operating several electricity plants, each with information that needs to be centralized and aggregated. This process is complicated with a system that includes 32 PI servers on separate networks, with different site owners and multiple data administrators.
Each site had solid monitoring in place for their facility, with turbine sensors reporting fuel consumption, power output, operating temperature, vibration and other key metrics. Collecting information across sites however, involved a largely manual process of accessing each PI server via VPN, querying the database, exporting files to the cloud, and aggregating the data. By the time a company-wide analysis was complete, it often represented information that was largely outdated.
TDengine was introduced to centralize this data and automate the process. Instances of TDengine for PI System were installed for each PI server and set to stream real-time data to TDengine Cloud. The occasionally spotty internet service doesn’t derail the process, as each TDengine PI Connector backfills any missing data once the service is re-established. This new system provides the team with a single dashboard to view data from all of the plants or drill down on a specific site or turbine.
In addition to centralization, TDengine Cloud acts as a powerful extension of their PI System with a range of data-sharing capabilities. This gives the team fine-grained control over the specific data to share with regulators and consultants, without having to provide full database access.
- Permissions: can be given organization-wide, for certain instances, for certain databases or for a specific data subscription topic.
- Data subscriptions: allow topics to be created from individual SQL queries to select data from a specific table, device or time period.
- Access: all the team needs to add someone to a topic is an email address – the subscriber can then access the data programmatically or replicate it to their own instance of TDengine.
Conclusion: Future-Proofing PI System
While many users love PI System, it’s had little development in recent years, partly due to multiple acquisitions which led to a significant loss in product knowledge and a divergence in development priorities.
TDengine provides a powerful extension of PI System that enhances its capabilities, enabling efficient data centralization and sharing without having to rip and replace a PI deployment. Organizations benefit from the freedom to use multiple systems at individual sites, using the right system for each site’s needs, and benefit from a unified view of their data.
Visit TDengine for PI System for information on how to easily centralize and share your PI System data.
