Pre-stress-integrated FEA for failure prediction in 3D-printed and injection-molded polymers

Abstract

PurposeThis study aims to improve the accuracy of failure prediction in polymer parts produced by additive manufacturing (AM) and injection molding (IM) by integrating manufacturing-induced residual stresses into finite element analysis (FEA). The main challenge addressed is the modeling of complex residual stress fields caused by anisotropy and non-uniform cooling. Despite this complexity, the proposed method improves simulation reliability, reduces prediction errors and more accurately identifies failure locations under mechanical loads.Design/methodology/approachThe study introduces the Adjacent Element Temperature-Driven Pre-Stress Algorithm (AETDPA), which embeds residual stresses into FEA using a breadth-first search-based mapping of thermal history. This approach enhances stress distribution accuracy and supports better fatigue life and structural durability predictions for fused deposition modeling and injection molded parts.FindingsApplying AETDPA significantly improves the accuracy of failure and deformation predictions by accounting for residual stresses often ignored in conventional FEA. The algorithm effectively captures anisotropy, layer-wise thermal behavior and manufacturing defects such as thermal strain and weld lines. Experimental validation through tensile and bending tests on acrylonitrile butadiene styrene and polylactic acid parts confirms the robustness and predictive capability of the approach.Originality/valueAETDPA overcomes key limitations of standard FEA by embedding process-induced stress effects directly into simulations. This enables more realistic stress profiles and fatigue predictions, contributing to improved design reliability and process control in critical applications, including automotive, aerospace and biomedical fields.