Abstract: A system for predictive assembly includes a model generator, a model analyzer, and an assembly planner. The model generator generates a first model of a first component and a second model of a second component before the first component and the second component are coupled together. The model analyzer analyzes the first model and the second model to determine a dimension of a gap between a first mating surface of the first component and a second mating surface of the second component after the first component and the second component are coupled together. The assembly planner recommends an action based on a comparison of the gap to a gap threshold.

Abstract: A system for automated sanding of a surface of a component includes a model generator, a model analyzer, and a path planner. The model generator is configured to generate a model representing at least a portion of a surface of a component. The model analyzer is configured to analyze the model to determine waviness of the surface. The path planner is configured to generate a sanding plan.

Abstract: The present disclosure provides a workflow engine for predictive assembly. In some aspects, the workflow engine is executed by one or more processors so that the one or more processors are configured to: receive a predictive assembly request for an assembly prediction to be generated for an assembly of interest; receive measurement data associated with the assembly of interest for which the assembly prediction is desired; autonomously build a workflow specific to the assembly of interest for generating the assembly prediction, wherein building the workflow includes determining i) which service pods of a plurality of service pods to invoke for generating the assembly prediction, and ii) a sequence of execution of the invoked service pods; autonomously generate the assembly prediction by executing the workflow using the invoked service pods and the measurement data; and output the assembly prediction.

Abstract: An electronic device includes at least one processor, at least one memory storing a model based definition (MBD) representing a model of a part, and an artificial intelligence (AI) client service. The AI client service, in response to execution by the at least one processor, is configured to receive inspection data corresponding to a cut part being fabricated based on the model of the part, compare the received inspection data to the MBD to determine any deviations of the cut part from the MBD, determine whether the cut part is defective based on the comparison, and update a digital thread corresponding to the part when the cut part is determined to be defective.

Abstract: An electronic device includes at least one processor, at least one memory storing a model based definition (MBD) representing a model of a part, and an artificial intelligence (AI) client service. The AI client service, in response to execution by the at least one processor, is configured to receive inspection data corresponding to a cut part being fabricated based on the model of the part, compare the received inspection data to the MBD to determine any deviations of the cut part from the MBD, determine whether the cut part is defective based on the comparison, and update a digital thread corresponding to the part when the cut part is determined to be defective.