Title: Surrogate Based Methods for Rapid Starting Point Optimization in Automated Fiber Placement

Authors: Alex Brasington, Christian Smith, Joshua Halbritter, Roudy Wehbe, Ramy Harik

DOI: 10.33599/nasampe/s.22.0705

Abstract: As the world of automated composites manufacturing continues to mature, Automated Fiber Placement (AFP) is proving to be a standout option for the manufacturing of large and complex structures. However, even with the recent advances in the AFP process, unavoidable defects still occur because of tool surface geometry, placement errors, or poor process planning. Defects can be minimized in the process planning phase by optimizing the selection of input parameters such as starting points, layup strategies, and tows per course. This input selection is typically done by hand with a seemingly infinite number of possibilities when considering all possible combinations of inputs, combined with expensive computational costs and a “black box” evaluation function. Such an optimization problem lends itself to the use of surrogate-based methods. The presented research evaluates multiple surrogate models for ply-by-ply starting point and layup strategy optimization. Each of the models’ performances are summarized, along with demonstrating the rapid nature of such an optimization technique when compared with other gradient-free options. Selected methods are used to optimize ply angles of 0, 45, -45, and 90 degrees on a doubly curved surface to evaluate the results of the optimization.

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Conference: SAMPE 2022

Publication Date: 2022/05/23

SKU: TP22-0000000705

Pages: 17

Price: $34.00