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.

Industrial data analytics in a cloud platform

A cloud-aware smart device that facilitates automated configuration and integration of the device within an automation system is provided. Upon installation within the automation system, the smart device determines its geographical location, identifies other devices on the system, and determines its role within the system. The smart device then establishes communication with a cloud platform running one or more cloud-based applications or services and sends a device profile containing the gathered information to the cloud platform. The device profile can be used to automatically configure the device for operation within the system or to add the smart device to an existing cloud-based application.

Smart device for industrial automation

A cloud-capable industrial device that provides time-stamped industrial data to a cloud platform is provided. The industrial device collects or generates industrial data in connection with monitoring and/or controlling an automation system, and includes a cloud interface that couples the industrial device to one or more cloud-based services running on a cloud platform. The industrial device can apply time stamps to respective items of industrial data reflecting a time that the data was measured or generated prior to providing the data to the cloud platform. To accurately reflect temporal relationships between data sets provided to the cloud platform from different locations and time zones, the industrial device can synchronize its internal clock with a clock associated with the cloud platform.

Time-stamping of industrial cloud data for synchronization

A cloud-based operator interface system is provided that runs as a cloud service on a cloud platform The cloud-based operator interface system collects industrial data from one or more industrial systems via respective cloud gateway devices A set of predefined operator interface screens are stored on cloud storage associated with the operator interface system, and delivered to authorized Internet-capable client devices upon request The industrial data received from the cloud gateways can be delivered to the client devices from the cloud platform via the operator interface screens Additional cloud-side services can correlate and analyzes the industrial data on the cloud platform to facilitate additional reporting, alarming, and notification features

Cloud-based operator interface for industrial automation

Embodiments of the present disclosure include systems and a method In one embodiment, a system is provided The system includes a risk calculation system configured to calculate a risk based on a static input and a dynamic input, and a decision support system configured to use the risk to derive a decision The system also includes a plant control system configured to update operations of a plant based on the decision, wherein the decision predicts future plant conditions

System and method for optimizing plant operations

A system may include a model library configured to model a safety system, wherein the model library comprises a plurality of subsystem models, and each of the plurality of subsystem models is configured to derive a reliability measure. The system further includes a fault tolerance input and a maintenance policy input. The system further includes a dynamic risk calculation engine (DRCE) configured to use a user-defined set of the plurality of subsystem models, the fault tolerance input and the maintenance policy input, to derive a system risk for an apparatus.

Systems and methods for improved reliability operations

A system includes a risk assessment system. The risk assessment system includes a risk calculation system configured to calculate a risk based on one or more static inputs and one or more dynamic inputs. The one or more dynamic inputs includes a location of a human resource, a mobile resource, or a combination thereof. The risk assessment system further includes a decision support system (DSS) configured to use the risk to derive one or more decisions based on the risk, the one or more static inputs, and the one or more dynamic inputs. The one or more decisions are configured to aid in operating an industrial facility.

Systems and methods for management of risk in industrial plants

A method (200) and system (300) of testing an overspeed protection system of a turbomachine may include providing an overspeed protection system on a turbomachine having at least one shaft. The method may: determine whether a permissive or permissive(s) is satisfied (210,215,225); initiate an overspeed test; automatically adjusting the speed of a shaft (235,240); determining if the speed exceeds an overspeed trip set point (120,255); and automatically disabling the automatic adjustment of the speed (275) after the test is complete.

Method and system for testing the overspeed protection system of a turbomachine

A system may include a dynamic risk calculation engine (DRCE) system. The DRCE includes a model library configured to model a system, wherein the model library comprises a plurality of subsystem models, and each of the plurality of subsystem models is configured to derive a reliability measure. The DRCE further includes a fault tolerance input and a maintenance policy input. The DRCE additionally includes a run-time risk calculation engine configured to use a user-defined set of the plurality of subsystem models, the fault tolerance input, and the maintenance policy input, to derive a system risk for an apparatus.

Systems and Methods For Dynamic Risk Derivation

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