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Addressing Data Flow Stability in PI Connector for Wonderware: Overcoming Store & Forward Challenges

Explore data flow stability challenges in PI Connector for Wonderware, especially post-Store & Forward events, with insights from experienced users.

Roshan Soni

4 min read

Addressing Data Flow Stability in PI Connector for Wonderware: Overcoming Store & Forward Challenges

In the ever-evolving landscape of industrial automation, seamless data flow between systems is crucial for maintaining operational efficiency. For organizations leveraging PI Connectors, such as the PI Connector for Wonderware, ensuring data flow stability is a critical concern. In this blog post, we delve into common challenges related to data consistency, particularly following "Store and Forward" (S&F) events, as shared by seasoned users of the PI System.

Understanding the Problem

David Chatel, a highly experienced user of the PI System, highlighted his encounters with periodic data flow inconsistencies using PI Connector for Wonderware. While typically stable, the connector seems to falter during periods characterized by abnormal S&F events. These events, which are designed to handle data discrepancies and ensure reliable data transfer during network issues, sometimes result in unanticipated data synchronization problems.

One of the key issues faced by users is synchronization between historical data restoration and real-time data, often necessitating manual CSV alterations to provoke history recovery. While this workaround can solve immediate problems, it is not a sustainable or efficient long-term strategy.

Insights from Experience

Another user, Steve, shared similar challenges, particularly slow propagation of changes from Wonderware Historian to PI, attributed to the history recovery process. His experience emphasizes a key insight: the importance of maintaining software compatibility and upgrading components like the Wonderware SDK and PI Connector to leverage performance improvements and bug fixes in newer versions.

Recommended Practices

Based on community insights and experiences shared by users like David and Steve, here are some recommended practices to enhance data flow stability in your PI System integration:

  1. Regular Updates: Ensure all components, including the PI Connector, Data Archive, and Wonderware SDK, are updated to the latest stable releases. This helps in capitalizing on resolved bugs and improved features.

  2. Compatibility Checks: Evaluate the compatibility of different software components in your setup. Discussions with support teams can provide clarity on known issues related to specific versions, facilitating proactive upgrades.

  3. Evaluate History Recovery Settings: Default settings for history recovery may not suit all operational contexts. Adjust these settings based on historical data needs and observe the impact on data synchronization.

  4. Automation Scripts for Recovery Tasks: Instead of manual CSV modifications, consider developing scripts or automation solutions to manage history recovery, making the process faster and less error-prone.

  5. Community Engagement: Active participation in community forums and discussion with peers can provide new perspectives and solutions to recurring challenges.

Conclusion

While PI Connector for Wonderware offers substantial benefits, addressing data flow stability issues requires a strategic approach. Integrating updated components, understanding the implications of history recovery settings, and leveraging community knowledge are pivotal in ensuring seamless data integration within your PI System.

As we rely increasingly on data-driven decision-making, overcoming these challenges not only improves system reliability but also enhances the overall efficiency of industrial operations. Stand by for further updates and insights as we continue to explore solutions and share experiences in the realm of PI System optimization.

Tags

#PI Connector
#Data Flow
#Wonderware
#Store and Forward
#Industrial Data
#Data Connectivity

About Roshan Soni

Expert in PI System implementation, industrial automation, and data management. Passionate about helping organizations maximize the value of their process data through innovative solutions and best practices.

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