A computer program, a computer-readable medium and to a system and method for checking an industrial facility formed as an automation facility, wherein real components of a provided real facility and/or data stemming from the real facility and/or simulated components of a provided simulated facility and/or data stemming simulated facility are manipulated using a computer program that includes at least one random algorithm, in particular during ongoing operation, such that random-based fault situations are caused in the real facility and/or the simulated facility.

A computer program, a computer-readable medium and to a system and method for checking an industrial facility formed as an automation facility, wherein real components of a provided real facility and/or data stemming from the real facility and/or simulated components of a provided simulated facility and/or data stemming simulated facility are manipulated using a computer program that includes at least one random algorithm, in particular during ongoing operation, such that random-based fault situations are caused in the real facility and/or the simulated facility.

The present disclosure relates to an online monitoring method of a nuclear power plant system based on an isolation forest method and a sliding window method. An isolation forest method used in the present disclosure is an abnormal detection model based on the idea of binary tree division, and has no requirements on the dimension and linear characteristics of monitoring data. In view of the characteristics of strong nonlinearity and high dimension of operation data of the nuclear power plant system, in the process of state monitoring, system abnormalities can be detected more quickly and accurately. In the present disclosure, a sliding window method is used to improve an isolation forest model, so that the improved isolation forest model has the functions of model online updating and real-time state monitoring, and the usability of an isolation forest state monitoring method is enhanced.

A semiconductor manufacturing apparatus including: a first device; one or more sensors; a first calculation circuit that calculates one or more feature quantities of the first device from the detected physical quantities; and a failure prediction circuit that compares the one or more feature quantities with a plurality of pieces of model data of a temporal change in one or more feature quantities until the first device fails, decides a piece of model data with the minimum difference from the calculated one or more feature quantities among the plurality of pieces of model data, calculates predicted failure time from a difference between a failure point in time and a point in time at which a difference from the calculated one or more feature quantities is the minimum in the piece of model data.

A programmable display device for a production system that includes a storage device and a plurality of the programmable display devices. The storage device includes a plurality of individual memory areas that store data from the plurality of the programmable display devices individually and are associated with any one of the plurality of the programmable display devices. There is a backup processing unit that loads some or all data that the programmable display device itself retains into an individual memory area associated with the programmable display device itself among the plurality of individual memory areas and a state management unit that updates state management information retained in the storage device when the backup processing unit has performed data update within the individual memory area associated with the programmable display device itself. The state management information indicates that data retained by the plurality of individual memory areas have been updated.

Described are platforms, systems, and methods for mapping data found in connected equipment from a manufacturer's selected schema, format, and protocol to a normalized data model. The platforms, systems, and methods identify a plurality of data sources associated with an automation environment; retrieve data from at least one of the identified data sources; generate a plurality of data source mapping profiles, each data source mapping profile specific to a particular data source configuration; maintain a data store comprising the plurality of data source mapping profiles; select a data source mapping profile specific to the at least one identified data source configuration; and apply an algorithm to map the retrieved data to a predetermined ontology based on the selected data source mapping profile for the at least one identified data source.

Described are platforms, systems, and methods for mapping data found in connected equipment from a manufacturer's selected schema, format, and protocol to a normalized data model. The platforms, systems, and methods identify a plurality of data sources associated with an automation environment; retrieve data from at least one of the identified data sources; generate a plurality of data source mapping profiles, each data source mapping profile specific to a particular data source configuration; maintain a data store comprising the plurality of data source mapping profiles; select a data source mapping profile specific to the at least one identified data source configuration; and apply an algorithm to map the retrieved data to a predetermined ontology based on the selected data source mapping profile for the at least one identified data source.

Described are platforms, systems, and methods to discover subtended devices through introspection of executive or supervisory controllers. The platforms, systems, and methods maintain a plurality of introspection directives, each introspection directive comprising a sequence of instructions specific to a communications protocol, the sequence of instructions comprising instructions to send at least one command to at least one controller associated with an automation environment in accordance with the communications protocol, instructions to receive a response to the at least one command, and instructions to parse the response; identify an appropriate introspection directive for the at least one controller; and execute the sequence of instructions with respect to the at least one controller to perform operations comprising: sending at least one command to at least one controller; receiving a response; and parsing the response.

Described are platforms, systems, and methods for real-time enrichment of vertices, edges, and related data within a graph database. The platforms, systems, and methods maintain a graph database comprising a representation of a current state of an automation environment comprising a plurality of data sources, wherein the data sources are represented as vertices in the graph database and relationships between the individual data sources are represented as edges in the graph database; operate a plurality of software agents, each software agent configured to perform operations comprising: applying an algorithm to identify patterns in the graph database; and generating a specific data enrichment based on one or more identified patterns; and contribute the generated data enrichment back to the graph database.

Described are platforms, systems, and methods to discover relationships among equipment in automated industrial or commercial environments by cycling each individual piece of equipment while observing sensors in all other equipment in order to measure how each part reacts to each other part. The platforms, systems, and methods identify a plurality of data sources associated with an automation environment; issue one or more commands to cycle a current data source in the a plurality of data sources; monitor the automation environment for events or state changes in the data sources; detect one or more events or one or more state changes in one or more other data sources in the a plurality of data sources; and determine one or more relationships between the current data source and the one or more other data sources.