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International Journal of AI for
Materials and Design AI applications in composite materials

A

B

C

Figure 7. Structure of XAI and research utilizing XAI in the field of composite materials. (A) Structure of XAI; (B) Analysis of the relationships between
design parameters of composite laminates and their impact on performance; (C) Methodology and results of utilizing XAI to analyze the delamination
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mechanisms of composites. 105
Abbreviations: FEM: Finite element method; LHS: Latin hypercube sampling; PDP: Partial dependence plot; SHAP: Shapley additive explanation; ViT:
Vision transformer; XAI: Explainable artificial intelligence.
load capacity, revealing the key factors that influence the material design, defect detection, and optimization of
material’s strength, such as the fiber tensile strength and manufacturing parameters. By combining ML with
cross-sectional area. explainability, XAI is advancing the development of more
These studies demonstrate the growing role of XAI efficient and transparent processes for the design and
in composite materials, providing critical insights for manufacture of composite materials.

Volume 2 Issue 3 (2025) 12 doi: 10.36922/IJAMD025210016