Citation

Malinverni, Eva Savina and R., Rajesh Sharma and Sungheetha, Akey (2026) Intelligent Adaptive 3D Printing Framework for Interactive Museum Artifact Replication: A Multi-Material Fabrication Approach with Embedded Sensory Feedback Systems. Procedia Computer Science, 282. pp. 1200-1213. ISSN 18770509

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Abstract

This study presents a theoretically grounded computational framework for adaptive multi-resolution three-dimensional scanning, heterogeneous material fabrication, and embedded tactile sensing, conceived entirely within theoretical science computing and extended numerical simulation. The system synthesises a six-camera hexagonal acquisition geometry, Poisson surface reconstruction, and radial basis function interpolation to replicate artefact geometry and surface properties at sub-millimetre fidelity. Structured light phase decoding across 48 Grey-code patterns yields depth uncertainty σz = 0.05 mm over a merged point cloud of 8.5 × 106 points, subsequently reduced via iterative closest point registration to mean residual 0.053 mm across six cloud pairs. Adaptive slicing reduces total layer count by 28–35 % relative to uniform minimum thickness while sustaining geometric fidelity exceeding 95 %. Multi-material deposition across a shore hardness range of 60A to 95D is governed by radial basis function hardness mapping achieving RMSE of 3.2 Shore units over 150 measurement sites, and CMYK colour reproduction encompasses 87 % of the sRGB gamut with mean perceptual difference ∆E2000 < 2.5 across 94 % of Munsell test patches. A 64-element force-sensitive resistor array embedded during fabrication achieves 0.01 N force resolution with power-law calibration R2 > 0.98. Theoretical validation confirms that the integrated pipeline attains 96.3 % dimensional accuracy, positioning the framework as a reproducible basis for digital heritage preservation, prosthetics prototyping, and autonomous robotic manipulation.

Item Type:	Article
Uncontrolled Keywords:	3D printing framework, museum artifact replication
Subjects:	N Fine Arts > NC Drawing Design Illustration
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	04 Sep 2026 03:50
Last Modified:	04 Sep 2026 03:50
URII:	http://shdl.mmu.edu.my/id/eprint/16706

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