The Boeing Company

Carla E Reynolds

Alexander Rubin

Samuel J Tucker

Phillip John Crothers

Steven Michael Shewchuk

Gregg Robert Bogucki

Troy Winfree

Andrew Lawrence Bauer

Joshua David Kalin

Dustin D Fast

A method of manufacturing a composite structure includes accessing design data for the composite structure that is manufactured according to a process including forming a layup of plies of fibers using a machine tool. The method includes applying the design data to an ANN classifier to classify a localized inconsistency of a type of inconsistency on the composite structure, the localized inconsistency spatially referenced to a location on the composite structure. The method includes performing a root cause analysis to identify one or more of process parameters as a potential cause of the type of inconsistency, and modifying one or more of the geometric model, the layup design, or values of the one or more of the process parameters to address the potential cause.

Composite manufacturing using data analytics

A system to aid in design for manufacturing an object includes a processor and a memory configured to store instructions. The processor is configured to receive first data representing a design of the object to be manufactured and second data representing a machine-learning model. The processor is configured to execute the instructions to generate third data using the first data and the second data. The third data indicates at least one of a modification to the design of the object or process conditions for production of the object. The processor is configured to send the design of the object, the process conditions, or both, to a manufacturing tool to enable production of the object. The machine-learning model is representative of production data and based at least partially on one or more of: object features, process parameters, environmental factors, and quality data.

Object design using machine-learning model

Growing community of inventors

Shawnee, KS, United States of America

Carla E Reynolds