Fabrication sequence optimization for minimizing distortion in multi-axis additive manufacturing

Wang, Weiming; Keulen, Fred van; Wu, Jun

doi:10.1016/j.cma.2023.115899

Cited by 8 publications

(1 citation statement)

References 44 publications

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“…Consequently, researchers underscore quality issues as the primary technological barrier hindering the wider industrial adoption of AM [ 3 , 4 , 5 ]. Intensive research has been conducted in recent years to mitigate this problem by detecting defects [ 6 , 7 ], enhancing part quality [ 8 ], and minimizing manufacturing errors [ 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

On-Machine LTS Integration for Layer-Wise Surface Quality Characterization in MEX/P

Fernández,

Zapico,

Blanco

et al. 2024

Sensors

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Material Extrusion (MEX) currently stands as the most widespread Additive Manufacturing (AM) process, but part quality deficiencies remain a barrier to its generalized industrial adoption. Quality control in MEX is a complex task as extrusion performance impacts the consistency of mechanical properties and the surface finish, dimensional accuracy, and geometric precision of manufactured parts. Recognizing the need for early-stage process monitoring, this study explores the potential of integrating Laser Triangulation Sensors (LTS) into MEX/P manufacturing equipment for layer-wise 3D inspections. Using a double-bridge architecture, an LTS-based sub-micrometric inspection system operates independently from the manufacturing process, enabling comprehensive digitization and autonomous reconstruction of the target layer’s topography. Surface texture is then computed using standardized indicators and a new approach that provides insight into layer quality uniformity. A case study evaluating two alternative extruder head designs demonstrates the efficacy of this integrated approach for layer quality characterization. Implementing a generalized layer-wise procedure based on this integration can significantly mitigate quality issues in MEX manufacturing and optimize process parameter configurations for enhanced performance.

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