Abstract: An industrial search and diagnosis system discovers available data items across heterogeneous data platforms that make up an industrial enterprise and indexes the data items in a unified searchable namespace. The system also indexes non-textual or multimedia input, including image data, video data, and audio data. This multimedia data can be indexed by the system in association with the relevant industrial systems (e.g., machines, automation systems, devices, production lines, etc.) so that the system can provide the multimedia data to the user when the relevant industrial systems are searched or invoked. The system also accepts and processes multimedia data from as search criteria or for diagnostic analysis. In an example analysis, users can submit images, audio, or video of an industrial machine or automation system, and the diagnosis system can identify an operational abnormality based on comparative analysis performed on the multimedia information.

Abstract: A layered industrial analytics architecture enables the flow of information from intelligent assets into tools and engines that perform analytics and enable decision-making in substantially real-time. The analytics architecture comprises analytic nodes that are distributed across multiple layers of an industrial enterprise, and includes system features that optimize movement of data across this layered architecture. Each analytic node includes base architectural constructs that host various analytic, data acquisition, and storage elements. These base constructs can operate autonomously, or in conjunction with other instances of base constructs or other elements of the control system. The system design uses a multi-platform compatible implementation that allows the base elements to be deployed on various different computing platforms.

Abstract: A layered industrial analytics architecture enables the flow of information from intelligent assets into tools and engines that perform analytics and enable decision-making in substantially real-time. The analytics architecture comprises analytic nodes that are distributed across multiple layers of an industrial enterprise, and includes system features that optimize movement of data across this layered architecture. Each analytic node includes base architectural constructs that host various analytic, data acquisition, and storage elements. These base constructs can operate autonomously, or in conjunction with other instances of base constructs or other elements of the control system. The system design uses a multi-platform compatible implementation that allows the base elements to be deployed on various different computing platforms.

Abstract: A cloud-based diagnosis and maintenance system facilitates discovery and indexing of plant-wide data residing on various data platforms across multiple industrial facilities. The system includes an indexing system that automatically inventories industrial devices and other data sources located throughout the facilities, and identifies available data items on each data source. The indexing system indexes the discovered data items in a federated data model that can subsequently be searched to locate data items or tags of interest. The diagnosis and maintenance system also includes analysis tools that facilitate cross-facility analysis of the data model, allowing performance metrics to be compared across similar automation systems at different facilities. The system can also generate recommendations for improving performance metrics based on results of the comparative analysis.

Abstract: A multi-platform industrial search system facilitates indexing and searching of plant-wide data residing on multiple different data platforms. The industrial search system automatically inventories industrial devices and other data sources located throughout a plant, and identifies available data items on each data source. The search system indexes the discovered data items in a federated data model that can subsequently be searched to locate data items or tags of interest. The federated data model records references to data items found on different types of data sources, including but not limited to industrial controller programs, human-machine interface applications, data historians, device documentation stores, inventory tracking systems, and other such data sources. The search system can also initiate automated searches of the federated data model in response to detected performance issues and deliver notifications and contextual information to plant personnel.

Abstract: An industrial control program development system allows a user to set metadata attributes for respective data items in the controller that indicate which of the data tags are to be monitored and collected by a separate industrial data historian system. When the industrial controller is deployed on a plant network, the data historian system reads the metadata attributes for the respective data items (e.g., data tags or data logs) defined in the controller and configures itself to collect and store data associated with the subset of data items that have been flagged for data collection. This system mitigates the need to manually configure the data historian with the identities of the data items that are to be monitored and collected for historical or reporting purposes.

Abstract: The subject matter disclosed herein relates generally to industrial automation systems, and, more particularly, to collecting video streams from a variety of video devices in an industrial environment, identifying and analyzing potential problems in the industrial environment using the video streams, and presenting the video streams and data associated with the potential problem to appropriate recipients.

Abstract: A multi-platform industrial search system facilitates indexing and searching of plant-wide data residing on multiple different data platforms. The industrial search system automatically inventories industrial devices and other data sources located throughout a plant, and identifies available data items on each data source. The search system indexes the discovered data items in a federated data model that can subsequently be searched to locate data items or tags of interest. The federated data model records references to data items found on different types of data sources, including but not limited to industrial controller programs, human-machine interface applications, data historians, device documentation stores, inventory tracking systems, and other such data sources. The search system can also initiate automated searches of the federated data model in response to detected performance issues and deliver notifications and contextual information to plant personnel.

Abstract: An automated industrial notification platform creates a link between a given industrial asset and one or more people or support entities qualified to provide support for the asset. An industrial device or machine stores electronic expert tag information that records and catalogues one or more support people or entities to be notified in response to detection of various types of performance or maintenance issues. The tag can include the experts' identities, contact information, roles relative to the industrial asset, event priorities, and other relevant information. Since the tag is stored in a memory location of the industrial asset, the tag travels with the asset so that experts are globally associated with the asset regardless of the asset's location. Notification components integrated with the industrial asset detect conditions that may require expert assistance, and send an automated notification to one or more experts identified by the tag information.

Abstract: A multi-platform industrial search and notification system performs automated and manually initiate information searches across multiple disparate industrial data platforms. The search system is built on a search platform that unifies plant-wide control system information from multiple diverse sources under a common namespace, or federated data model. The system can monitor this federated data model for conditions that may warrant attention by plant personnel, and deliver proactive notifications and operational data to selected users via their personal devices. The system can customize presentation of this data based on the user's role, location, and/or other contextual information. To this end, the system can automatically generate user-specific and context-specific dashboards, widgets, or other visualizations, and render these custom visualizations to the user at appropriate times.

Abstract: Techniques to facilitate pinning information in an industrial automation environment are disclosed herein. In at least one implementation, a pinboard associated with an asset of the industrial automation environment is displayed on a display system of a computing system, wherein the pinboard includes a plurality of entries comprising content associated with the asset. A user request is received to add a new entry to the pinboard comprising additional content associated with the asset. The user request is transferred to an application server, wherein the application server processes the user request to add the new entry to the pinboard.

Abstract: A cloud-based operator training system includes a snapshot management architecture, which provides a hybrid system for generation of control system level scenarios and system-state snapshots, and which can improve the fidelity of a training simulation. By implementing the simulation system on a cloud platform, the system can generate a large and growing set of snapshot files representing various control states and corresponding process states. These files can then be leverage during operator training sessions to yield high fidelity simulated system operation.

Abstract: A multi-platform industrial search system facilitates indexing and searching of plant-wide data residing on multiple different data platforms. The industrial search system automatically inventories industrial devices and other data sources located throughout a plant, and identifies available data items on each data source. The search system indexes the discovered data items in a federated data model that can subsequently be searched to locate data items or tags of interest. The federated data model records references to data items found on different types of data sources, including but not limited to industrial controller programs, human-machine interface applications, data historians, device documentation stores, inventory tracking systems, and other such data sources. The search system can present search results as a layered map presentation that graphically depicts the search results on multiple view-specific layers that can be viewed individually or combined into composite layered presentations.

Abstract: A multi-platform industrial search system facilitates indexing and searching of plant-wide data residing on multiple different data platforms. The industrial search system automatically inventories industrial devices and other data sources located throughout a plant, and identifies available data items on each data source. The search system indexes the discovered data items in a federated data model that can subsequently be searched to locate data items or tags of interest. The federated data model records references to data items found on different types of data sources, including but not limited to industrial controller programs, human-machine interface applications, data historians, device documentation stores, inventory tracking systems, and other such data sources. The search system can also initiate automated searches of the federated data model in response to detected performance issues and deliver notifications and contextual information to plant personnel.

Abstract: An industrial data indexing system facilitates discovery and indexing of plant-wide data residing on multiple different data platforms. The indexing system automatically inventories industrial devices and other data sources located throughout a plant, and identifies available data items on each data source. The indexing system indexes the discovered data items in a federated data model that can subsequently be searched to locate data items or tags of interest. The federated data model records references to data items found on different types of data sources, including but not limited to industrial controller programs, human-machine interface applications, data historians, device documentation stores, inventory tracking systems, and other such data sources. The indexing system also discovers and records interdependencies between data items, which can be used to improve relevancy of search results returned to the user.

Abstract: A first attribute is associated with a first data storage device and a second attribute is associated with a second data storage device. The first data storage device stores first time series data and the second data storage device stores second time series data. In parallel, the first attribute is applied to the first time series data and the second attribute is applied to the second time series data. The application is effective to cause an alteration of one or more of the first time series data or the second time series data. The alteration may be a thinning or reduction of the time series data.

Abstract: A plurality of analytics in a cloud-based environment is accessed. Each of the plurality of analytics performs an operation on time series data. Within the cloud-based environment, a selected one or more of the plurality of analytics is chosen. A set of time series data is uploaded to the cloud-based environment and the selected one of the plurality of analytics is optimized on that set of time series data.