Title: INTEGRATION OF DESIGN DATA INTO AUTOMATED FIBER PLACEMENT PROCESS PLANNING METRICS

Authors: Alex Brasington, Joshua Halbritter, August Noevere, Ramy Harik

DOI: 10.33599/nasampe/s.23.0020

Abstract: With the ever-expanding aviation industry, a need is arising for more rapid production of composite aircraft to meet increasing demand. State-of-the-art aircraft such as the Boeing 787 showcase 50% composite material usage by weight, highlighting this emerging industry-wide adoption of the material system. Currently, many of the large structures associated with these aircraft are manufactured additively via Automated Fiber Placement (AFP). The AFP process shows great potential for efficient manufacturing, however unavoidable defects still occur because of tool surface geometry, placement errors, or poor process planning, resulting in decreased quality and throughput. Due to such effects, it is critical to incorporate design for manufacturing (DFM) principles to achieve the optimal manufacturing plan and resulting structure. This work will develop a methodology for incorporating design information into process planning metrics in an automated fashion to achieve an optimal set of process inputs. The analysis incorporates HyperX, Computer Aided Process Planning (CAPP) and Vericut Composite Programming (VCP). Safety margins from HyperX are imported into CAPP where AFP defects are mapped to the values. The resulting margins are then incorporated into the CAPP manufacturability algorithms, creating a design informed process planning analysis.

References: [1] “FAST (Flight Airworthiness Support Technology) - Special Edition: A350 XWB,” Airbus Technical Magazine, 2013. [2] J. Hale, “Boeing 787: From the Ground Up,” Aero Magazine, 2008. [3] R. Harik, Z. Gurdal, C. Saidy, S. J. Williams, and B. Grimsley, “Automated Fiber Placement Defect Identity Cards: Cause, Anticipation, Existence, Significance, and Progression,” in SAMPE 2018, 2018. Accessed: Mar. 24, 2020. [Online]. Available: https://www.researchgate.net/publication/326464139 [4] C. Sacco et al., “On the effect of manual rework in AFP quality control for a doubly-curved part,” Compos B Eng, vol. 227, 2021, doi: 10.1016/j.compositesb.2021.109432. [5] A. Noevere and C. Collier, “Mapping Manufacturing Data for Stress Analysis of Automated Fiber Placement Structures,” in 2018 AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, AIAA SciTech Forum, 2018. doi: 10.2514/6.2018-0228.c1. [6] A. Noevere, C. Collier, and R. Harik, “Integrated Design and Manufacturing Analysis for Automated Fiber Placement Structures,” in SAMPE 2019, 2019. [7] A. Noevere, C. Collier, R. Harik, and J. Halbritter, “Development of a Design for Manufacturing Tool for Automated Fiber Placement Structures,” in AIAA Scitech 2019 Forum, 2019. [8] A. Noevere and C. Collier, “Design for manufacturing tool for automated fiber placement structures – verification and validation,” in AIAA Scitech 2020 Forum, 2020. doi: 10.2514/6.2020-1477. [9] G. Rousseau, R. Wehbe, J. Halbritter, and R. Harik, “Automated fiber placement path planning: A state-of-the-art review,” Comput Aided Des Appl, vol. 16, no. 2, pp. 172–203, 2019, doi: 10.14733/cadaps.2019.172-203. [10] J. A. Halbritter, “Automation of Process Planning for Automated Fiber Placement,” University of South Carolina, 2020. [11] J. Moore, A. Colvin, S. Ghose, and B. Johnson, “Design for Manufacturing: Laminate Focused Design and Analysis Tools for Automated Composites Manufacturing,” in SAMPE 2019 - Charlotte, NC, 2019. doi: 10.33599/nasampe/s.19.1478. [12] A. Brasington, J. Halbritter, R. Wehbe, and R. Harik, “Bayesian optimization for process planning selections in automated fiber placement,” J Compos Mater, vol. 2022, no. 0, pp. 1–22, 2019, doi: 10.1177/00219983221129010. [13] A. Brasington, C. Smith, J. Halbritter, R. Wehbe, and R. Harik, “Surrogate Based Methods for Rapid Starting Point Optimization in Automated Fiber Placement,” in SAMPE 2022 Conference Proceedings, 2022. [14] S. Maneewongvatana and D. M. Mount, “Analysis of Approximate Nearest Neighbor Searching with Clustered Point Sets,” 1999. [15] P. Virtanen et al., “SciPy 1.0: fundamental algorithms for scientific computing in Python,” Nat Methods, vol. 17, pp. 261–272, 2020, doi: 10.1038/s41592-019-0686-2. [16] Collins Aerospace, “Nacelle Systems,” https://www.collinsaerospace.com/what-we-do/industries/commercial-aviation/aerostructures/nacelle-systems, 2022. [17] Y. Blanchard, “Composites design optimization for automated fiber placement process,” in SAE Technical Papers, Sep. 2014, vol. 2014-September, no. September. doi: 10.4271/2014-01-2261.

Conference: SAMPE 2023

Publication Date: 2023/04/17

SKU: TP23-0000000020

Pages: 17

Price: $34.00