The Boeing Company

Philip L Stubblefield

Sudhakar Y Reddy

Kenneth W Fertig

Adriana Willempje Blom-Schieber

Troy Winfree

Rainer Johannes Romatka

A layup strategy analysis tool including a memory storing layup strategy analysis instructions and one or more processors configured to execute the layup strategy analysis instructions. During execution, the layup strategy analysis instructions obtain model data representing a three-dimensional (3D) model of an object to be formed using an automated fiber placement process. The layup strategy analysis instructions also obtain process data descriptive of the automated fiber placement process and one or more automated fiber placement machines. The layup strategy analysis instructions also generate output indicating a count of a number of tows that can be simultaneously applied during a single pass based on a geometry of the object and based on manufacturability constraints indicated by the process data.

Layup strategy analysis

A method of determining a conditional computational plan for a data dependent constraint network represented by a bipartite graph containing input variable nodes, output variable nodes, and relation nodes, may include specifying, using a variable node specifier, at least one output variable node for which a plan is desired. The method may further include determining, using a plan determiner, a plan from the input variable nodes to the output variable node using a backward chaining search of the bipartite graph.

System and method for computational planning in a data-dependent constraint management system

Multi-Objective Optimization (MOO) is integrated with a Constraint Management System (CMS) so as to rapidly and flexibly search large design spaces and focus on 'interesting' designs as determined by user-specified criteria. A method embeds a trade space and its trade-off envelope within the same CMS network used to calculate the values of the points in the trade space itself. The method supports automatic variation of the resulting trade-off analyses in response to variations in upstream parameters, assumptions, and/or requirements. When feasible, the CMS can back-solve for values of upstream parameters so that selected attributes of the trade-off envelope achieve user-specified values. The coupled use of a CMS with multi-objective optimization avoids having to generate a large set of permutations of inputs and factors and then restricting the analysis to those having desired outputs or of having to manually 'reformulate' the equation set so that it solves in the desired direction.

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Federal Way, WA, United States of America

Philip L Stubblefield