Exemplified herein is a graphical user interface for an industrial automation system that provides, in a single aggregated and eloquent view, a configuration workspace to discover and present configuration details of control components within an industrial automation system. These components may include industrial controllers, programmable logic controllers (PLCs), supervisory control and data acquisition (SCADA) systems, programmable automation controllers (PACs), and the like, which have modules (as well as submodules) connected thereto. Among other things, the configuration workspace enables a holistic view of identified hardware configuration and the modular reconciliation and troubleshoot of the network device and module configurations.

Exemplified herein is a graphical user interface for an industrial automation system that provides, in a single aggregated and eloquent view, a configuration workspace to discover and present configuration details of control components within an industrial automation system. These components may include industrial controllers, programmable logic controllers (PLCs), supervisory control and data acquisition (SCADA) systems, programmable automation controllers (PACs), and the like, which have modules (as well as submodules) connected thereto. Among other things, the configuration workspace enables a holistic view of identified hardware configuration and the modular reconciliation and troubleshoot of the network device and module configurations.

An industrial integrated development environment (IDE) includes a training component that improves the IDE's automated design tools over time based on analysis of aggregated project data submitted by developers over time. The industrial IDE can apply analytics (e.g., artificial intelligence, machine learning, etc.) to project data submitted by developers across multiple industrial enterprises to identify commonly used control code, visualizations, device configurations, or control system architectures that are frequently used for a given industrial function, machine, or application. This learned information can be encoded in a training module, which can be leveraged by the IDE to generate programming, visualization, or configuration recommendations. The IDE can automatically add suitable control code, visualizations, or configuration data to new control projects being developed based on an inference of the developer's design goals and knowledge of how these goals have been implemented by other developers.

An industrial integrated development environment (IDE) includes a training component that improves the IDE's automated design tools over time based on analysis of aggregated project data submitted by developers over time. The industrial IDE can apply analytics (e.g., artificial intelligence, machine learning, etc.) to project data submitted by developers across multiple industrial enterprises to identify commonly used control code, visualizations, device configurations, or control system architectures that are frequently used for a given industrial function, machine, or application. This learned information can be encoded in a training module, which can be leveraged by the IDE to generate programming, visualization, or configuration recommendations. The IDE can automatically add suitable control code, visualizations, or configuration data to new control projects being developed based on an inference of the developer's design goals and knowledge of how these goals have been implemented by other developers.

A highly versatile process control or factory automation field device is configured with an interface and communication connection structure and security features that enable the field device to operate as a data server that communicates with and supports multiple different applications or clients, either directly or indirectly, while simultaneously performing standard process and factory automation control functions in a highly secure manner. The security features include a root of trust component, a secure boot component, secure memory components, secure communication components, security audit components, secure provisioning components and endpoint identity components, making the field device communications and operations secure and trustworthy. Moreover, various different process control and factory automation network architectures and, in particular, communication architectures, support the versatile field device to enable the versatile field device to simultaneously communicate with multiple different client devices or applications (each associated with a different system) via a common communication network infrastructure in a very secure manner, using the same or different communication protocols.

Systems and methods for sorting livestock including a livestock processing station, a computer network system, and a livestock routing mechanism. The livestock processing station confines the individual livestock, allowing individual livestock data to be collected and analyzed. The computer network system includes a programmable logic controller (PLC) for data input at the livestock processing station and a sorting application coupled to the PLC via a computer network, the sorting application for analyzing individual livestock data and assigning livestock to pens.

A program fragmentation unit (131) divides a target program into fragments according to groups of processing. A fragment group extraction unit (132) extracts, from among sets of fragments, each set in which instruction groups match between fragments, as a fragment group. A functionalization candidate extraction unit (136) extracts, from among sets of fragment groups, a set in which instruction groups match between fragment groups, usage patterns of a variable group match between the fragment groups, and types of variables match between the fragment groups, as a functionalization candidate. An output unit (140) outputs information on the functionalization candidate.

A control device calculates a specified quantile in stored data relating to a load applied on a spindle, as a target spindle load, and controls a feed speed of the spindle as to a work, so that the measured load applied on the spindle is the calculated target spindle load. A user can set the target spindle load with the load on the spindle measured in a state in which the work is being stably machined as a reference.

Provided is an intelligent correction device control system for a super-resolution lithography precision mask, including: a sixteen-way pneumatic fine-tuning mask deformation control subsystem configured to deform a mask, detect a force value of a mask deformation, compare the force value of the mask deformation with an output force set value, and generate a first control feedback quantity to adjust a force deforming the mask, so as to control a deformation quantity of the mask; and an alignment subsystem configured to acquire images of the mask and a substrate, and adjust a position between the mask and the substrate according to the images, so as to align the mask with the substrate.

A system and method for detecting a failure in a redundant signal path during operation of the redundant path is disclosed. A test signal is sequentially injected into each signal path while an input signal is conducted by the other signal path not receiving the test signal. The test signal is selected at a frequency to verify operation of a filter connected in series along each path. A processor generates the test signal, injects the test signal at the input of the filter, and receives the output of the filter. The processor then generates a frequency response of the filter in each signal path as a function of the output from the filter and of the original test signal. The frequency response obtained along each of the redundant signal paths is compared to each other to detect a failure of one of the filters present along the respective signal paths.