An intelligent identification and warning method for an uncertain object of a production line in a digital twin environment, includes: establishing a model library for uncertain physical objects from a non-production line system; adding attribute data to the uncertain physical objects from the non-production line system; importing an established model library and added attribute data for the uncertain physical objects from the non-production line system into a model library of an existing DT production line system; performing auto-detection on an uncertain physical object entering a production line system; performing auto-detection on an actual size of the uncertain physical object entering the production line system; warning a danger for an unsafe object by means of voice prompting, system alarming and information pushing; matching a corresponding three-dimensional (3D) model in the established model library for a safe object; and loading a matched 3D model to the DT production line system.

A method for virtually testing a system control process for a process engineering system and a simulation device for virtually testing the system control process, wherein at least one preconfigured control module for controlling a component of the system is provided and the system control process is generated based on this control module and the control of the process engineering system is additionally simulated by the generated system control process, where at least one value of an input parameter of the system control process is predefined by a component-specific simulation model, and where the component-specific simulation model is contained in the preconfigured control module.

An agricultural working machine with a driver assistance system is disclosed. The driver assistance system controls driving functions of the agricultural working machine and at least one working assembly of the agricultural working machine in the context of performing a work process. The driver assistance system accesses a set of rules in the form of control strategies to control the at least one work assembly according to a specific control strategy. The driver assistance system includes an interface to communicate with an external computer unit, which is remote from the agricultural working machine, and through which data can be exchanged between the driver assistance system and the external computer unit. For example, the driver assistance system receives data from the external computer unit via the interface during the work process of the agricultural working machine, and selects the control strategy for performing the work process based on the data.

A system and method for learning and/or optimizing processes related to semiconductor manufacturing is provided. A learning component generates a set of candidate process models based on process data associated with one or more fabrication tools. The learning component also selects a particular process model from the set of candidate process models that is associated with lowest error. An optimization component generates a set of candidate solutions associated with the particular process model. The optimization component also selects a particular solution from the set of candidate solutions based on a target output value and an output value associated with the particular solution.

An agricultural working machine with a driver assistance system is disclosed. The driver assistance system controls driving functions of the agricultural working machine and at least one working assembly of the agricultural working machine in the context of performing a work process. The driver assistance system accesses a set of rules in the form of control strategies to control the at least one work assembly according to a specific control strategy. The driver assistance system includes an interface to communicate with an external computer unit, which is remote from the agricultural working machine, and through which data can be exchanged between the driver assistance system and the external computer unit. For example, the driver assistance system receives data from the external computer unit via the interface during the work process of the agricultural working machine, and selects the control strategy for performing the work process based on the data.

An industrial workflow tracking and identification system captures optimal employee workflows for addressing maintenance issues or operating industrial systems, and renders these workflows at appropriate times in order to guide operators and maintenance personnel through optimal sequences for carrying out operations or addressing maintenance issues. The system monitors and indexes both plant-wide system data as well as employee behaviors, and identifies correlations between operational outcomes and user workflows. In this way, the system tracks and captures optimal employee workflows for addressing particular maintenance issues, performing certain procedures, or achieving preferred production outcomes. By identifying and recording correlations between observed employee behaviors and production outcomes, the system creates a library of best practices that can be used as a training tool, as well as to provide substantially real-time guidance to maintenance staff and operators in connection with solving a problem or performing a task.

An industrial workflow tracking and identification system captures optimal employee workflows for addressing maintenance issues or operating industrial systems, and renders these workflows at appropriate times in order to guide operators and maintenance personnel through optimal sequences for carrying out operations or addressing maintenance issues. The system monitors and indexes both plant-wide system data as well as employee behaviors, and identifies correlations between operational outcomes and user workflows. In this way, the system tracks and captures optimal employee workflows for addressing particular maintenance issues, performing certain procedures, or achieving preferred production outcomes. By identifying and recording correlations between observed employee behaviors and production outcomes, the system creates a library of best practices that can be used as a training tool, as well as to provide substantially real-time guidance to maintenance staff and operators in connection with solving a problem or performing a task.

An adaptive engine and a method of adaptive control are disclosed. The method comprises receiving an input regressor, where the input regressor comprises a reference signal, a system output measurement, and a control output. The method includes applying one or more estimation laws to the input regressor to estimate two or more sets of estimated model parameter tensors, ; receiving two or more possible control signals; generating two or more estimated system outputs; and selecting a control signal from a set comprising at least the first possible control signal and the second possible control signal, or a combination of possible control signals blended from two or more of the sets.

An adaptive engine and a method of adaptive control are disclosed. The method comprises receiving an input regressor, where the input regressor comprises a reference signal, a system output measurement, and a control output. The method includes applying one or more estimation laws to the input regressor to estimate two or more sets of estimated model parameter tensors, ; receiving two or more possible control signals; generating two or more estimated system outputs; and selecting a control signal from a set comprising at least the first possible control signal and the second possible control signal, or a combination of possible control signals blended from two or more of the sets.