(101b) Osisoft: Providing Foundational Infrastructure to Enable Organizational Layers of Analytics

At OSIsoft, we believe that people with data can transform their world. But which people and what data? How does that data become information, and how does that information translate to action? The digitation of modern business has resulted in the development of new computing platforms with large-scale storage and powerful tools, many self-service, providing rapid analytical results. Efforts to improve manufacturing processes through advanced analytics have existed for years, however these recent innovations have redoubled efforts in applying this technology to the manufacturing space.

Providers, platforms, and applications vary but successful scenarios require four common features. They are:

• Reliable real-time data collection from manufacturing assets at the edge or from control systems.
• Consistent data stored at the edge, on-prem, or in the cloud.
• Augmentation model for configuring descriptive features and supplying context for both asset association and process condition.
• Accessibility to all tools use by contributing analysts from within and outside the organization.

These features can only be supplied by taking an infrastructure approach to plant data collection and storage. A consistent data infrastructure spanning from edge to cloud provides a solid foundation to companies building their layers of business and operations analytics.

As organizations mature in their use of data, the infrastructure enables growth by:

• Providing a foundation to understand their data. Analytical efforts are built on verified and trusted data - reliable data sources, accurate descriptions, consistent units of measure, and optimized frequency of measurement.
• Adding context to data. The capable infrastructure connects to other operations systems to add metadata to real-time measurements. Data relationships are formed between maintenance information, lab sample data, engineering standards, and other contextual sources to enrich real-time data from operations.
• Using this data awareness for first law process calculations, event detection, and organizational KPI’s that stream in real-time. These calculations enable those first sets of analyses by helping users define what happened and why.
• Integrating with powerful statistical and artificial intelligence tools that build on the streaming analytics to provide predictive and prescriptive content about the process.

To each tool its best purpose. The PI System provides a real-time data infrastructure and contextual capability to enable customers on their analytics journey.