Multivariate Monitoring and Evaluation of Dimensional Variability in Additive Manufacturing: A Comparative Study of EBM, FDM, and SLA

Abstract

This study evaluates AM dimensional performance using multivariate quality control methods. Three-dimensionally printed products include multivariate correlated quality characteristics (QCs) that should be evaluated together. Furthermore, the same 3D-printed product can be produced by various additive manufacturing techniques, necessitating a comparative analysis to figure out which process provides superior quality. This study evaluates three AM processes—electron beam melting (EBM), fused deposition Modeling (FDM), and stereolithography (SLA)—to assess their performance in multivariate quality control. The research methodology focuses on monitoring, evaluating, and comparing these three AM processes. A standardized benchmark specimen is designed and fabricated using each AM process. Seven critical dimensional QCs were identified, and their specification limits were established based on ISO standards. Data collection was conducted using a high-precision measurement technique. This study used an improved Multivariate Exponentially Weighted Moving Average (MEWMA) control chart for process monitoring to detect deviations. The subsequent process evaluation used Multivariate Process Capability Indices (MPCIs) to assess conformance to specification limits. Then, a sensitivity study was conducted to assess the variability within each AM process. The findings identify the QC that contributes most to variation in each AM process and show clear differences in dimensional performance among EBM, SLA, and FDM, supporting process selection for precision applications.