Optimization of 3D‑Printed Patterns Parameters and Two‑Stage Burnout Process for Defect Reduction in Propeller Blades Investment Casting Shell Mold

Authors

Zolkarnain Marjom

Facuty of Industrial & Manufacturing Technology & Engineering, Universiti Teknikal Malaysia Melaka (Malaysia)

Ahmad Syazani Ahmad Moktar

Facuty of Industrial & Manufacturing Technology & Engineering, Universiti Teknikal Malaysia Melaka (Malaysia)

Mohamad Ridzuan Mohamad Kamal

Facuty of Industrial & Manufacturing Technology & Engineering, Universiti Teknikal Malaysia Melaka (Malaysia)

Article Information

DOI: 10.47772/IJRISS.2025.91200055

Subject Category: Technology

Volume/Issue: 9/12 | Page No: 633-641

Publication Timeline

Submitted: 2025-12-10

Accepted: 2025-12-17

Published: 2025-12-31

Abstract

This study investigates the optimization of 3D-printed investment casting patterns and two-stage burnout parameters to minimize defects in propeller blade manufacturing. A full factorial design of experiments (2⁴) was implemented to analyze the effects of four fused deposition modeling (FDM) parameters—shell thickness, infill density, layer height, and internal pattern structure—on burnout performance. Thirty-two PLA patterns were fabricated and evaluated through a two-stage burnout process: Stage 1 (200–350 °C) assessed air permeability, while Stage 2 (up to 650 °C) examined surface integrity using dye penetrant testing and visual crack inspection. Statistical analysis using GLM ANOVA revealed that air permeability exhibited no significant main effects but was influenced by higher-order interactions, notably Infill× Shell× Pattern (F = 5.067, p = 0.03879) and Layer× Shell× Pattern (F = 6.975, p = 0.01779). Dye penetrant indications were dominated by shell thickness (F = 2135.9, p ≈ 1.84e⁻18), with layer height and multiple interactions also significant. Visual cracking was strongly associated with shell thickness (Fisher exact p = 0.00245), with 1 mm shells reducing defects compared to 2 mm. The findings underscore that shell thickness is the primary factor for Stage 2 defect mitigation, while Stage 1 optimization requires joint tuning of shell, infill, and pattern parameters. The proposed two-stage burnout workflow enables early identification of critical factor combinations, offering a robust approach for improving dimensional integrity and surface quality in additively manufactured investment casting applications.

Keywords

Additive Manufacturing; Investment Casting; Two‑Stage Burnout

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