A control apparatus records commands and information about execution time of industrial machinery. The control apparatus analyzes a program, and when a command that requires preparation time exists in the program, then calculates advanced preview command time by subtracting the preparation time from time to start the execution of the command based on the execution time previously recorded. The control apparatus outputs in advance the command requiring the preparation time when the advanced preview command time comes, so as to shorten the preparation time.

Systems and methods for providing operator variation analysis for an industrial operation are disclosed herein. In one aspect of this disclosure, a method for providing operator variation analysis includes processing input data received from one or more data sources to identify transient or non-steady state process data relating to the industrial operation and selecting one or more types of data in the transient or non-steady state process data to cluster for operator variation analysis. The one or more types of data are clustered using one or more data clustering techniques, and the clustered one or more types of data are analyzed to identify a best operator of a plurality of operators responsible for managing the industrial operation. Information is analyzed to determine if one or more gaps exist in the economic operation of the industrial operation due to operator variability between the best operator and other operators.

Systems and methods for providing operator variation analysis for an industrial operation are disclosed herein. In one aspect of this disclosure, a method for providing operator variation analysis includes processing input data received from one or more data sources to identify steady state process data relating to the industrial operation and selecting one or more types of data in the steady state process data to cluster for operator variation analysis. The one or more types of data are clustered using one or more data clustering techniques, and the clustered one or more types of data are analyzed to identify a best operator of a plurality of operators responsible for managing the industrial operation. Information is analyzed to determine if one or more gaps exist in the economic operation of the industrial operation due to operator variability between the best operator and other operators.

Systems and methods for addressing gaps in an industrial operation due to operator variability are disclosed herein. In one aspect of this disclosure, a method for addressing gaps in an industrial operation due to operator variability includes processing input data received from one or more data sources to identify a best operator of a plurality of operators responsible for managing the industrial operation, and determining if one or more gaps exist in the economic operation of the industrial operation due to operator variability between the best operator and operators other than the best operator. Identified gaps may be analyzed to determine if relevant characteristics associated with the gaps justify at least one solution for addressing the gaps for the particular industrial operation. At least one solution may be identified and mapped to the gaps in some instances.

Configuring distributed control in an industrial system comprises building an asset model representative of a process control installation of the industrial system and creating an asset library of distributed control assets according to a distributed control programming standard. The asset model includes modeled assets defined according to levels of a physical model standard and representing physical devices of the industrial system. The distributed control assets each have one or more predefined, built-in facets. One of the distributed control assets in the asset library is mapped to each of the modeled assets to configure the process control installation of the industrial system and generate an asset-based control application for providing distributed control of the industrial system. Additional aspects relate to auto-creation of control applications based on an information model, either through the use of machine learning or an asset configurator tool.

A data collection system for an industrial machine, the data collection system comprising circuitry configured to: collect collection data relating to the industrial machine based on a predetermined collection setting; identify the predetermined collection setting based on identification information associated with the collection data; and execute parse processing relating to the collection data based on the identified predetermined collection setting.

A sensor kit that is configured for monitoring an industrial setting includes an edge device and a plurality of sensors that capture sensor data and transmit the sensor data via a self-configuring sensor kit network. At least one sensor can capture sensor measurements and output instances of sensor data, generate and output reporting packets, and transmit the reporting packets to the edge device via the self-configuring sensor kit network in accordance with a first communication protocol. The edge device receives reporting packets from the plurality of sensors via the self-configuring sensor kit network and transmits sensor kit packets to a backend system via a public network, wherein the sensor kit packets are based on a compressed block of media content frames indicative of the sensor data.

A method for monitoring an industrial setting using a sensor kit having a plurality of sensors and an edge device including a processing system can include receiving, by the processing system, reporting packets from one or more respective sensors of the plurality of sensors, wherein each reporting packet includes routing data and one or more instances of sensor data; generating, by the processing system, a block of media content frames, wherein each media content frame includes a plurality of frame values, each frame value being indicative of a respective instance of sensor data; compressing, by the processing system, the block of media content frames using a media codec to obtain a compressed block; generating, by the processing system, one or more server kit packets based on the compressed block; and transmitting, by the processing system, the one or more server kit packets to a backend system via a public network.

A system can include a backend system and a sensor kit configured to monitor an industrial setting. The sensor kit can include an edge device and a plurality of sensors that capture sensor data and transmit the sensor data via a self-configuring sensor kit network. At least one sensor can capture sensor measurements and output instances of sensor data, generate and output reporting packets, and transmit the reporting packets to the edge device via the self-configuring sensor kit network in accordance with a first communication protocol. The edge device receives reporting packets from the plurality of sensors via the self-configuring sensor kit network and transmits sensor kit packets to the backend system via a public network. The backend system can include a processing system and a storage system, where the processing system performs backend operations on the sensor data and the storage systems stores the sensor data.

A method for monitoring an underwater industrial setting using a sensor kit having a plurality of sensors and an edge device can include receiving, by an edge processing system of the edge device, reporting packets from the plurality of sensors via a self-configuring sensor kit network. Each reporting packet can include routing data and one or more instances of sensor data. The method can further include performing one or more edge operations on the sensor data and generating one or more sensor kit packets based on the edge operations. The method can include transmitting the sensor kit packets to a backend system via a public network.