Title: Foreign Object Debris (FOD) in Composites Fabrication: Detection, Correction and Prevention

Authors: Chris Page, Scott Blake

DOI: 10.33599/nasampe/c.23.0112

Abstract: The fabrication methods and internal structure of composite materials make them particularly susceptible to performance degradation from entrapped foreign object debris (FOD). FOD that goes undetected until final inspection at the end of the fabrication cycle, known as an “internal escape,” results in costly scrap or rework. External escapes, in which FOD remains undetected within a composite structure in the field, can and have resulted in the catastrophic loss of aircraft, including loss of life. Identifying and eliminating FOD before it is embedded between composite plies has been one of the highest priorities of the composites industry, and it takes on even greater importance as adhesive-bonded composite joints gain popularity over mechanically fastened joints. This paper reviews technologies and methods used to detect and correct FOD events while the FOD is still on the surface and easily removed from a composite work-in-progress (WIP), ranging from manual inspection to electrical detection of metallic peel ply. It will then present a novel in-situ inspection technology based on machine vision and digital image analysis. This technology has achieved near-100% detection of FOD as small as 3 mm across on large, complex composite surfaces. Data from this inspection technology may be used in Industry 4.0 systems for analysis and future prevention of similar FOD events.

References: 1. J. Ransom, E. Glaessgen, I. Raju, N. Knight and J. Reeder, “Lessons Learned from Recent Failure and Incident Investigations of Composite Structures,” 49th AIAA/ASME/ASCE/ AHS/ASC Structures, Structural Dynamics, and Materials Conference, April 2008. DOI: 10.2514/6.2008-2317. 2. The FOD Control Corporation, “Controlling FOD in a Manufacturing Facility,” self-published article, https://www.fodcontrol.com/controlling-fod-in-a-manufacturing-facility/, accessed June 9, 2023. 3. E. Gregory and P. Juarez, “In-situ Thermography of Automated Fiber Placement Parts,” AIP Conference Proceedings 2018. DOI: 10.1063/1.5031551. 4. J. Ritter and J. Sjogren, “Real-time Infrared Thermography Inspection and control for Automated Composite Material Layup,” U.S, Patent 7,513,964 (April 2009). 5. C. Schmidt, B. Denkena, K. Voltzer and T. Hocke, “Thermal Image-Based Monitoring for the Automated Fiber Placement Process,” Procedia CIRP 62: 27-32 (2017). 6. U. Khan, J. Iqbal and M. Khan, “Automatic Inspection System Using Machine Vision,” 34th Applied Imagery and Pattern Recognition Workshop (APR’05), 2005, pp. 6-217. DOI: 10.1109/AIPR.2005.20. 7. S. Blake, “Generating Good Data for AI-Based Automatic Inspection and Remediation of Large-Scale Composite Components,” SAMPE 2023 Conference, April 2023. DOI: 10.33599/nasampe/s.23.0149 8. G. Nguyen, S. Dlugolinsky, M. Bobák et al., “Machine Learning and Deep Learning Frameworks and Libraries for Large-Scale Data Mining: A Survey,” Artif Intell Rev 52, 77–124 (2019). DOI: 10.1007/s10462-018-09679-z. 9. S. Fahle, C. Prinz and B. Kuhlenkötter, “Systematic Review on Machine Learning (ML) for Manufacturing Processes – Identifying Artificial Intelligence (AI) Methods for Field Application,” 53rd CIRP Conference on Manufacturing Systems Proceedings 93 (2020), 413–418. 10. S. Blake, “Elements and Mechanisms for Applying Artificial Intelligence to Composites Fabrication, SAMPE 2019 Conference. DOI: 10.33599/nasampe/s.19.1435.

Conference: CAMX 2023

Publication Date: 2023/10/30

SKU: TP23-0000000112

Pages: 10

Price: $20.00