Abstract: A configuration management interface system is provided for standardizing communication between an external application and one or more hardware or emulated industrial controllers. The interface system reads one or more industrial control programs and presents available data tags defined by the control programs to a user via an interface screen. The user can select a subset of the available data tags that are to be exposed to the external application for data communication. Based on the selected data tags, controller configuration information read from the control programs, and additional configuration information provided by the user, the interface system generates a control unit file that acts as a communication bridge between the external application and the selected data tags residing on the industrial controllers. The control unit file can be used to interface the application (e.g., an industrial simulation or another type of application) with either hardware controllers or emulated controllers.

Abstract: A boiler control system executing on a cloud platform facilitates remote control system analysis and generation of suitable set point parameters for a given boiler application. The system includes a system interface component, a modeling component and a correlation analytics component. The system interface component collects industrial data associated with a set of boilers and demand data associated with a set of loads. The system interface component also stores the industrial data and the demand data on a cloud platform. The modeling component generates a boiler behavioral model for storage on the cloud platform based on analysis of the industrial data and the demand data. The boiler behavioral model defines at least one correlation between efficiency and capacity associated with the set of boilers. The correlation analytics component determines at least one set point parameter for the set of boilers based on analysis of the boiler behavioral model.

Abstract: A cloud gateway device facilitates collection of industrial data from one or more data sources on the plant floor and migration of the collected data to a cloud platform for storage and processing. The cloud gateway device collects historical, live, and/or alarm data directly from industrial devices networked to the gateway device, formats and encapsulates the data with customer-specific header information, and sends the resulting data packets to a cloud platform for processing by cloud-level analytics services. To keep local memory requirements low, the cloud gateway device supports store-and-forward functionality in the event of a communication loss to the cloud platform, whereby the collected industrial data is redirected to an external data storage repository until communication to the cloud platform is reestablished.

Abstract: Cloud-based data processing services facilitate collection and processing of industrial data in a cloud platform. On-premise data collection agents collect and pre-process industrial data from one or more data sources, including industrial devices, historians, etc. The agents apply a header to the data defining a hierarchical, customer-specific data model that can be leveraged in the cloud platform to suitably process the data. Cloud-side data process services receive the resulting data packets, assign the data to one or more priority queues, and invoke a manifest assembly corresponding to the data model defined by the header. The manifest assembly defines one or more operations to be performed on the received data, including specifying a final storage destination for the data, determining one or more metrics for an industrial system or process based on the received data, or other such operations.

Abstract: A cloud agent facilitates collection of industrial data from one or more data sources on the plant floor and migration of the collected data to a cloud platform for storage and processing. Collection services associated with the cloud agent perform on-premise data collection of historical, live, and/or alarm data directly from industrial devices networked to the agent or from intermediate data concentrators that gather the data from the devices. Queue processing services executed by the cloud agent package the data into a data packet comprising header information that identifies a customer associated with the industrial enterprise, processing priority information, and other information that informs data processing services on the cloud platform how to process and/or direct the incoming data. The cloud agent then establishes a communication channel to the cloud platform and sends the data via the channel.

Abstract: A cloud human-machine interface (HMI) generation system converts an original HMI project to a web-compatible version of the HMI capable of storage and execution on a cloud platform or web server. The cloud HMI generation system parses HMI project files exported from the original HMI to identify graphical objects and their attributes, animations, data tags linked to the HMI, and other characteristics of the HMI. The system then generates scripts or function calls that reproduce the identified graphical objects and their associated animations, yielding a web-based HMI that emulates the original HMI project. The resulting cloud HMI can retrieve copies of the original industrial system data maintained on cloud-based storage, allowing the cloud HMI to display near real-time system data on a client device from any location.

Abstract: A cloud-based global alarm annunciation broker assist in locating and contacting suitable technical support personnel in response to detected alarm events at a plant facility. The system comprises a cloud-based framework that dynamically matches on-site alarm events to domain experts capable of addressing the alarm events. The framework uses an agent-based architecture to gather industrial data from data sources within the industrial environment, including time-series alarm data. The data is received at a cloud platform, where broker services perform a global search for suitable technical support resources in response to alarm events identified by the collected data. The brokering system can automatically generate service tickets and send notifications to both end users and system managers/supervisors, and can notify application-level experts about events and anomalies that emerge from the on-premise processes being monitored by the cloud-based broker system.

Abstract: A control loop tuning system executing on a cloud platform facilitate remote control system analysis and generation of suitable controller gains for a given closed-loop control application. The system leverages cloud-side analytics and a gain correlation model generated based on historical data collected from the industrial control system and maintained on cloud storage. The gain correlation model creates a virtual association between controller gains and process variables based on operational and configuration data collected from the industrial control system. The system then applies iterative analytics to the model to converge on a set of controller gains determined to satisfy an optimization criterion. The recommended controller gains are then provided to a client device for review and implementation in the real system controller.

Abstract: Authentication of cloud agents that collect and/or process industrial data facilitates secure communications with a cloud platform. An authentication component receives an authentication request from a cloud agent device residing at an industrial facility. The authentication component also authenticate the cloud agent device in response to the authentication request for a defined period of time based on an access key that uniquely identifies the cloud agent device residing at the industrial facility. A cloud data processing component receives, at a cloud platform, one or more data packets from the cloud agent device during the defined period of time and processes industrial data contained in the one or more data packets according processing instructions associated with the cloud platform.

Abstract: Systems, methods, and software to facilitate cloud-based data processing and analysis in an industrial automation environment are disclosed herein. In at least one implementation, operational data generated by at least one industrial machine is stored in a local cache. The operational data is transferred for storage in an unstructured data storage system in a cloud-based architecture. In the cloud-based architecture, the operational data is processed to convert the operational data to a structured format and the operational data in the structured format is then stored in a structured data storage system. In response to receiving a request for analytics, at least a portion of the operational data is extracted from the structured data storage system and the analytics are executed on the at least the portion of the operational data.

Abstract: A remote asset server allows an industrial asset (e.g., a controller, motor drive, etc.) to be remotely and securely monitored and managed by an owner of the industrial asset as well as other relevant entities, such as original equipment manufacturers (OEMs). The remote asset server acts as a network infrastructure device that regulates access to the industrial asset by different entities in accordance with security policies defined by an end user. These defined security policies are implemented in a cloud platform as role-specific portals by a connectivity broker, the portals serving as secure connection pipelines to the industrial asset via the remote asset server. Using this architecture, an end user can define which aspects of an industrial asset are allowed to be remotely viewed, accessed, or modified by outside entities such as OEMs or system integrators.

Abstract: An industrial attestation service executing on a cloud platform collects industrial data from multiple levels of an industrial enterprise and identifies subsets of the industrial data that characterize normal operation. In the cloud platform, baselines are generated for diverse aspects of the industrial enterprise based on the identified subsets, where the baselines characterize normal operation. The baselines are used as a reference in connection with device and system attestation. Aspects of the industrial enterprise that deviate from their corresponding baselines are identified in the cloud platform. Attestation reports indicating aspects of the enterprise that have altered relative to their baselines are delivered to client devices via the cloud platform.

Abstract: A cloud-based predictive maintenance service collects industrial data from multiple industrial customers for storage and analysis on a cloud platform. The service analyzes data gathered from multiple customers across different industries to identify operational trends as a function of industry type, application type, equipment in use, device configurations, and other such variables. Based on results of the analysis, the predictive maintenance service predicts anticipated device failures or system inefficiencies for individual customers. Notification services alert the customers of impending failures or inefficiencies before the issues become critical. The cloud-based notification services also notify appropriate technical support entities to facilitate proactive maintenance and device management.

Abstract: A remote technical support system leverages a cloud platform to automate technical support interactions, facilitating rapid diagnosis and solution of detected performance issues in industrial systems. The technical support system facilitates automated collection of relevant system data from a customer's industrial assets in the event of a detected performance issue requiring involvement of a technical support entity. The relevant system data can be sent to the cloud platform in response to a manual request for support at the plant floor, or automatically in response to detection of a possible device failure or performance issue. The cloud-based remote technical support system then routes the data to a suitable remote support representative, providing the representative with information about customer's industrial system and operations that may be relevant in connection with diagnosing the issue.

Abstract: Cloud-aware industrial devices feed robust sets of data to a cloud-based data analyzer that executes as a service in a cloud platform. In addition to industrial data generated or collected by the industrial devices, the devices can provide device profile information to the cloud-based analyzer that identifies the device and relevant configuration information. The industrial devices can also provide customer data identifying an owner of the industrial devices, contact information for the owner, active service contracts, etc. The cloud-based data analyzer leverages this information to perform a variety of custom analytics on the data and generate reports or notifications catered to the particular industrial assets' optimal performance and business goals of the owner's industrial enterprise, as well as perform real-time decision making and control.

Abstract: A cloud-based risk assessment service collects industrial data from multiple relevant and connected sources for storage and analysis on a cloud platform. The service analyzes gathered data from internal and external sources and customers across different industries to identify operational trends as a function of industry type, application type, equipment in use, device configurations, and other such variables. Based on the analysis, the risk assessment service identifies risk factors inherent in a customer's particular industrial enterprise. The cloud-based system generates a risk profile for the customer that identifies the determined risks and recommends risk aversion strategies based on the customer's specific profile, compared to industry standards, product information, internal business expectations, external regulatory bodies, and/or past performance.

Abstract: A cloud-based remote monitoring system and method monitor an industrial facility. The industrial facility includes one or more industrial devices. A cloud agent located at the industrial facility is configured to, by at least one processor, collect data indicative of a past and/or a present state of the industrial devices according a manifest specific to the industrial facility. The cloud agent is further configured to send the collected data to a remote cloud platform according to the manifest dynamically reconfigure the cloud agent without interrupting the collecting and the sending. The cloud platform processes the sent data to facilitate remote monitoring of the industrial devices.