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

Guardado en:

Detalles Bibliográficos
Publicado en:	Processes vol. 13, no. 12 (2025), p. 3825-3847
Autor principal:	Al-Ahmari, Abdulrahman M
Otros Autores:	Moath, Alatefi, Ameen Wadea
Publicado:	MDPI AG
Materias:	Mechanical properties Fused deposition modeling Accuracy Comparative analysis Transplants & implants Performance evaluation Quality control Optimization Control charts Factorial experiments Process planning Monitoring Manufacturing Additive manufacturing Variability Polymers Comparative studies Electron beam melting Research methodology Capability indices Specifications Process controls Research design Multivariate analysis Process selection Control methods Lithography
Acceso en línea:	Citation/Abstract Full Text + Graphics Full Text - PDF
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Descripción
Resumen:	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.
ISSN:	2227-9717
DOI:	10.3390/pr13123825
Fuente:	Materials Science Database