Abstract: A system includes a void filter that receives sensor data employed to produce or inspect a manufactured part, the void filter generates a void data subset indicating voids detected in the manufactured part. A stress analyzer processes the void data subset from the void filter and determines coordinate data and force data for the respective detected voids in the manufactured part. At least one deterministic model analyzes the coordinate data and the force data from the stress analyzer determined for the detected voids from the void data subset. The deterministic model analyzes failure of the detected voids with respect to time and generates deterministic output data indicating failure over a deterministic timeframe. A prognostic analyzer processes the deterministic output data from the at least one deterministic model and generates a failure prediction for the as manufactured part.

Abstract: One example includes a repair assembly that is comprised of a composite patch, an adhesive, and a veil. The adhesive is disposed between a composite structure that includes an anomaly to be repaired and the composite patch and the composite patch. The veil is disposed between the composite structure and the composite patch. The veil generates heat in response to electric power being applied to the veil, with the adhesive being cured with the heat generated with the veil to repair the composite structure including the anomaly.

Abstract: A process and device for 3D printing parts incorporating long-fiber reinforcements in an advanced composite material is disclosed. A nozzle for a 3D printing device receives a polymer material and a reinforcing fiber through separate inlets. A passage from the reinforcing fiber inlet cleaves the passage containing the polymer material, creating an interstitial cavity into which the reinforcing fiber is introduced. The polymer material closes back on itself and encapsulates the reinforcing fiber, then drags the fiber along with the flow and exits nozzle to be deposited on a work surface or part being manufactured.

Abstract: A method and apparatus for embedding critical data directly onboard a physical asset is disclosed. Since the critical data and the asset are never separated, accurate and timely data pertinent to the asset travels with it, and may be written, read, and updated. Accurate data collection ensures a digital model/twin of the asset reflects the true physical state of the asset. Data is embedding optically or magnetically and may be read or rewritten so that information about the life/usage of the asset is continually available, right up to the current state.

Abstract: A process and device for 3D printing parts incorporating long-fiber reinforcements in an advanced composite material is disclosed. A nozzle for a 3D printing device receives a polymer material and a reinforcing fiber through separate inlets. A passage from the reinforcing fiber inlet cleaves the passage containing the polymer material, creating an interstitial cavity into which the reinforcing fiber is introduced. The polymer material closes back on itself and encapsulates the reinforcing fiber, then drags the fiber along with the flow and exits nozzle to be deposited on a work surface or part being manufactured.

Abstract: A method and apparatus for embedding critical data directly onboard a physical asset is disclosed. Since the critical data and the asset are never separated, accurate and timely data pertinent to the asset travels with it, and may be written, read, and updated. Accurate data collection ensures a digital model/twin of the asset reflects the true physical state of the asset. Data is embedding optically or magnetically and may be read or rewritten so that information about the life/usage of the asset is continually available, right up to the current state.

Abstract: A system includes a physical layer that a plurality of data structures that represents a plurality of physical input data associated with product materials, assemblies, and operational use of a product of interest over various stages of product lifetime. The system includes reasoning model layer to process the data structures for the respective product stages to determine uncertainty descriptor data (UDD) for each product stage. The system includes a propagation layer that employs a plurality of virtual models that electronically describe each stage in the plurality of product stages with the UDD from each stage and propagates the UDD from each updated virtual model from each product stage between each of the plurality of virtual models across a network to mitigate compounding of error estimates across each product stage of the product lifetime to provide a product lifetime estimate.