Abstract: A method includes training a machine learning model on a training data set, that describes input parameters to and corresponding output parameters from manufacturing equipment, using at least one learning algorithm to obtain a physics model that describes evolution of a state space of the manufacturing equipment, configuring a machine-learning-based controller agent to generate commands for the physics model that modify settings of a simulation of the manufacturing equipment by the physics model such that, responsive to input data, the physics model generates corresponding predicted output parameters, and training the machine-learning-based controller agent on the settings and corresponding predicted output parameters using at least one other learning algorithm.

Abstract: Following activation of a first machine, a standardized structured data model is instantiated in a controller of the first machine that describes the first machine according to predefined categories populated with predefined labels that are indicative of measured parameters of the first machine, components of the first machine, and subsystems of the first machine.

Abstract: A fluid connector and method for measuring an operating parameter of a fluid conduit is disclosed. The fluid conduit includes a conduit wall enclosing a fluid channel wherein a fluid flows through the fluid channel from a first opening to a second opening. At least one sensor element is embedded within the conduit wall along the direction of the fluid channel between the first opening and the second opening that is used to measure the operating parameter.

Abstract: One or more processors generate a feature set describing evolution of a state space of a manufacturing system from time series data of sensors measuring values of control parameters and exogenous parameters of the manufacturing system, and measuring values of feature parameters of components produced by the manufacturing system. The one or more processors also generate from the feature set predicted values of at least one of the feature parameters, and alter at least one of the control parameters according to the feature set and the predicted values to drive the predicted values toward a target value or target values.