Smart Process Planning for Automated Fiber Placement

Author

• Matthew J. Godbold, Clemson UniversityFollow

Date of Award

8-2026

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Automotive Engineering

Committee Chair/Advisor

Ramy Harik

Committee Member

Saeed Farahani

Committee Member

Robert Prucka

Committee Member

Vinita Jansari

Abstract

Automated Fiber Placement (AFP) is a preeminent manufacturing technology for producing high-performance composite structures, offering precise material placement, reduced waste, and the potential for highly optimized lightweight designs. While AFP has been widely adopted in aerospace applications, its broader use across industries such as automotive, wind energy, maritime, and sporting goods remains limited. A key barrier to wider adoption is the traditional separation of design, manufacturing, and inspection processes, which drives up cost and results in inefficiencies, sub-optimal designs, and limited feedback between lifecycle stages. In current practice, manufacturing is treated as an isolated process, disconnected from early-stage design decisions and post-production inspection data. This siloed approach attenuates the potential of AFP to deliver fully optimized, defect-minimized composite structures.   This dissertation addresses these limitations by developing the Integrated Smart Process Planning (iSPP) framework for AFP, which supersedes the traditional manual, a posteriori approach with a closed-loop, data-driven process. While current AFP process planning is heavily dependent on tacit knowledge and offers little systematic feedback between stages, the iSPP framework transforms this workflow into a smart, adaptive, and interconnected process. It guides manufacturing decisions by reconciling original design intent with real-world production data.   The research is realized through the development of a set of integrated capabilities that collectively form the iSPP framework. Each capability was designed to address a specific gap in the AFP lifecycle while interfacing seamlessly to create a cohesive, end-to-end process. At the core is the Computer-Aided Process Planning (CAPP) software, which semi-automates process planning decisions and manages ply- and laminate-level data to enable informed trade-offs between manufacturing feasibility and design intent. Building on this foundation, novel defect scoring algorithms were developed to quantify manufacturing quality in a way that supports optimization and decision-making. These feed into ply-level optimization methods that combine global surveying with a local perpendicular shift approach to minimize in-plane defects. For laminate-level optimization, two complementary approaches are presented: a stagger-based method that systematically distributes starting points to reduce through-thickness defect alignment, and a gravity-based model derived from an analogy to Newton's law of universal gravitation that quantifies spatial defect interactions to minimize through-thickness stacking while protecting margin-critical areas. To bridge design and manufacturing, the platform integrates with Collier Aerospace's HyperX to incorporate structural margin-of-safety data directly into defect scoring, and with Vericut Composite Programming (VCP) to automate ply generation, perform defect prediction, and produce NC programs. Finally, the platform incorporates inspection data to compare as-manufactured and as-designed panels. The full capability is demonstrated through verification and demonstration on the Quartic benchmark surface, a doubly-curved saddle geometry provided by Collier Aerospace as a challenging AFP process planning test case. The CAPP-driven approach was compared to manual planning baselines, demonstrating intentional control over defect placement, improved process planning efficiency, and the potential for structural performance benefits through margin-informed optimization.   The results demonstrate that integrating design, manufacturing, and inspection into a unified AFP process planning platform enables intentional, data-driven control over build quality and defect distribution. By embedding defect awareness, structural performance considerations, and inspection feedback into a single, adaptive environment, the iSPP framework reduces reliance on empirical methods and lowers the barrier to adoption across diverse industries. This lifecycle-integrated approach provides a foundation for next-generation AFP systems that are more accessible, adaptable, and capable of delivering high-quality composite structures across a broad range of manufacturing domains.

Recommended Citation

Godbold, Matthew J., "Smart Process Planning for Automated Fiber Placement" (2026). All Dissertations. 4394.
https://open.clemson.edu/all_dissertations/4394

Author ORCID Identifier

0000-0001-8056-9122