Residual Stress Mitigation and Distortion Control in Laser Powder Bed Fusion Components for High-Reliability Engineering Applications

Abstract

This study examined residual stress mitigation and distortion control in Laser Powder Bed Fusion (LPBF) components for high-reliability engineering applications. The problem addressed was the limited quantitative evidence on how process instability, residual stress, distortion, post-processing, and inspection jointly influence LPBF component reliability. The purpose was to determine whether these control practices significantly predict reliability outcomes in demanding engineering cases such as aerospace, biomedical, automotive, energy, defense, and precision tooling applications. A quantitative, cross-sectional, case-based design was used with 150 valid responses from additive manufacturing engineers, materials engineers, quality assurance professionals, design engineers, reliability/process engineers, and academic specialists. The key variables were process parameter stability, residual stress mitigation, distortion control, post-processing treatment, quality assurance and inspection, and LPBF component reliability. Data were analyzed using descriptive statistics, Cronbach’s alpha reliability testing, Pearson correlation, multiple regression, and hypothesis testing. The findings showed high agreement across all major constructs, with post-processing treatment recording the highest mean score (M = 4.18), followed by residual stress mitigation (M = 4.11), LPBF component reliability (M = 4.07), distortion control (M = 4.03), quality assurance and inspection (M = 3.96), and process parameter stability (M = 3.89). The research instrument was reliable, with an overall Cronbach’s alpha of 0.892. Correlation results showed significant positive relationships between reliability and post-processing treatment (r = 0.704), residual stress mitigation (r = 0.681), distortion control (r = 0.653), quality assurance (r = 0.625), and process stability (r = 0.603), all at p < 0.01. Regression analysis confirmed that the model explained 59.7% of the variance in LPBF component reliability, R² = 0.597, F (5,144) = 42.67, p < 0.001. Post-processing treatment was the strongest predictor (β = 0.312), followed by residual stress mitigation (β = 0.286) and distortion control (β = 0.241). The study implies that reliable LPBF manufacturing requires integrated process control, stress reduction, distortion management, post-processing, and inspection systems.