Expert Consensus on Post-Processing Techniques for Enhancing the Visual Appearance of FDM 3D-Printed Parts Using the Fuzzy Delphi Method

Mohd Haidiezul Jamal Ab Hadi; Mohd Shahrizal Dolah; Saiful Hasley Ramli; Khairul Manami Kamarudin; Muhammad Aiman Ahmad Fozi

doi:10.58915/aset.v5i1.3254

Authors

Mohd Haidiezul Jamal Ab Hadi Universiti Malaysia Perlis
Mohd Shahrizal Dolah Universiti Putra Malaysia
Saiful Hasley Ramli Universiti Putra Malaysia
Khairul Manami Kamarudin Universiti Putra Malaysia
Muhammad Aiman Ahmad Fozi Universiti Malaysia Perlis

DOI:

https://doi.org/10.58915/aset.v5i1.3254

Keywords:

Additive manufacturing, Automotive exterior parts, Fused Deposition Modeling (FDM), Fuzzy Delphi Method, Surface Finishing

Abstract

The growing use of Fused Deposition Modeling (FDM) for automotive exterior components is constrained by poor surface quality and the “staircase effect,” which fails to meet “Class A” visual standards. To overcome fragmented, trial-and-error manual finishing, this study uses the Fuzzy Delphi Method (FDM) to establish an expert-driven consensus framework. An eleven-member panel evaluated 36 items across six themes using a 7-point Likert scale, which was converted into triangular fuzzy numbers. The findings show that finishing is an interdependent system in which mechanical and chemical sequences govern light reflection, thereby dictating paint smoothness and gloss. Mechanical sandblasting with angular aluminum oxide (A = 0.821) serves solely as a preparatory step to level the substrate topography and optimize bonding morphology. This establishes an anchor for chemical finishing, where standardized automotive coating systems, including 2K primers, layer thickness control, and topcoat distribution (A), drive final visual enhancements. These layers eliminate micro-voids, directly optimizing glossiness and aesthetic quality. Ultimately, this transition leads to a standardized engineering pathway, accelerating commercial FDM integration while advancing sustainable manufacturing practices (SDG 9 and SDG 12).

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