A software defined distributed control system (SDCS) in a process plant includes an application layer that includes a plurality of containers instantiated in a data cluster. Each of the containers is an isolated execution environment executing within the local operating system of a respective computing node. The containers cooperate to facilitate execution of a control strategy in the SDCS, and includes a hyper converged infrastructure (HCI) operating across the data cluster, which HCI is configured to communicate with the application layer via an adapter service. The HCI includes software-defined (SD) compute resources, SD storage resources, SD networking resources, and an orchestrator service. The orchestrator service is programmed to configure a first container to include a service executing within the first container. It also assigns the first container to execute on an available hardware resource to control a plurality of field devices operating in the process plant.

A problem is to specify a more proper manufacturing process for a product as a material. A configuration of the present invention for solving the above problem is a manufacturing process optimization system 1 which includes an input device 12 which receives a final product and information on its manufacturing process, a central control device 11 which in accordance with a product management unit 21 stored in a main storage device 14, separates each process block constituting the manufacturing process into functions that the process thereof is responsible for, and selects the sensitivity of each separated function along the manufacturing process to thereby calculate process conditions in all manufacturing process, and an output device 13 which outputs the process conditions.

A method for correlating data from sensors includes receiving sensor information from a plurality of sensors of an industrial operation. Sensor information from component sensors is used for functionality of a component of the industrial operation and sensor information from additional sensors monitor conditions of a portion of the industrial operation different from the component. The method includes deriving, using the sensor information, correlations between component sensors and additional sensors and deriving a baseline signature from the sensor information and the correlations. The baseline signature encompasses a range of normal operating conditions. The method includes identifying an abnormal operating condition based on a comparison between additional sensor information and the baseline signature. The sensor information is used differently for functionality of the component than for deriving the correlations and baseline signature and identifying the abnormal operating condition. The method includes sending an alert with the abnormal operating condition.

A model-based industrial security policy configuration system implements a plant-wide industrial asset security policy in accordance with security policy definitions provided by a user. The configuration system models the collection of industrial assets for which diverse security policies are to be implemented. An interface allows the user to define zone-specific security configuration and event management policies for a plant environment at a high-level based on a security model that groups the industrial assets into security zones. When new industrial devices are subsequently installed on the plant floor, the system determines whether a security policy defined by the model is applicable to the new device and commissions the new device to comply with any relevant security policies. This mitigates the necessity for a system administrator to manually configure individual devices to comply with plant-wide security policies.

A cyber-physical system may have monitoring nodes that generate a series of current monitoring node values over time that represent current operation of the system. A hierarchical abnormality localization computer platform accesses a multi-level hierarchy of elements, and elements in a first level of the hierarchy are associated with elements in at least one lower level of the hierarchy and at least some elements may be associated with monitoring nodes. The computer platform may then determine, based on feature vectors and a decision boundary, an abnormality status for a first element in the highest level of the hierarchy. If the abnormality status indicates an abnormality, the computer platform may determine an abnormality status for elements, associated with the first element, in at least one level of the hierarchy lower than the level of the first element. These determinations may be repeated until an abnormality is localized to a monitoring node.

A number of communications for transmitting update data from a control device to a client is decreased, and discrepancies in the content of the latest update data between the control device and the client are prevented. The control device has: an update data monitoring unit for monitoring the latest update data and monitoring whether there has been an update within a predetermined time thereafter; an update data confirmation unit which, if there has been no update in the predetermined time, transmits to the client a request to confirm an update data reception state; a reception state determination unit which, based on the update data reception state in the client and the latest update data, determines whether the client has received the latest update data; and a retransmission instructing unit which, if the client has not received the latest update data, re-transmits the latest update data to the client.

The present invention extends to methods, systems, and computer program products for recording, sharing, and trading industrial process-related information via distributed ledgers. A program defines an industrial process to be performed at an industrial machine. The industrial machine is activated performing the industrial process in accordance with the program. Industrial process data is collected during and corresponding to performance of the industrial process. The industrial process data is stored to a distributed ledger as a component of a smart contract associated with performing the industrial process. It is determined that the industrial data was stored to the distributed ledger in a timely and accurate fashion. An amount of token is added to an account of a machine operator in response to determining that the process data was stored to the distributed ledger in a timely and accurate fashion.

A method for security and safety of an industrial operation includes receiving sensor information from a plurality of sensors of an industrial operation. Sensor information from at least a portion of the plurality sensors is used for functionality of a plurality of components of the industrial operation. The method includes monitoring data traffic of the industrial operation, and deriving a baseline signature from the sensor information. The baseline signature encompasses a range of normal operating conditions. The method includes identifying an abnormal operating condition of the industrial operation based on a comparison between additional sensor information from the plurality of sensors and the baseline signature and identifying an abnormal data traffic condition. The method includes determining that the abnormal operating condition correlates to the abnormal data traffic condition, and sending a security alert in response to determining that the abnormal operating condition correlates to the abnormal data traffic condition.

A system for dynamically load-balancing at least one redistribution element across a group of computing resources that facilitates at least an aspect of an Industrial Execution Process in an M:N working configuration is illustrated. The system is configured to: access from a central or distributed data store, a configuration component operational data and capabilities or characteristics associated with the M:N working configuration; identify a load-balancing opportunity to trigger redistribution of a redistribution element to a redistribution target selected from a redistribution target pool defined by remaining computing resource components associated with the M:N computing resource working configuration; select at least one redistribution target for redeployment; redeploy the at least one redistribution element to the redistribution target; determine redeployment to the at least one selected redistribution target to be a viable redeployment; and execute the Industrial Execution Process utilizing the at least one redistribution element at the selected redistribution target.

A sensor data input device obtains a plurality of sensor data sequences, each indicating time-series sensor values generated by measuring a work of a working subject using a sensor. A class data generator determines a plurality of intervals obtained by temporally dividing each sensor data sequence based on the sensor values, determines classes of the intervals, each class indicating a type of temporal variations in the sensor values included in one of the intervals, and generates a plurality of first class data sequences for each sensor data sequence, each first class data sequence indicating the intervals and the classes of the sensor data sequence. A class data linker associates the corresponding intervals having an identical class with each other, among the plurality of first class data sequences. A determiner calculates characteristic values of the intervals associated with each other.