Achieving 17-4 PH parts with comparable performance to high-investment technologies through a multivariable Doehlert design optimization and material extrusion

Other authors

Universitat Ramon Llull. IQS

Publication date

2025-06-27



Abstract

Purpose: This study aims to optimize Metal Additive Manufacturing (MAM) via Material Extrusion (MEX) using desktop equipment to produce high-performance 17-4 PH stainless steel parts. This research seeks to address the underexplored extrusion process parameters that hinder optimization in this field, contributing to a deeper understanding of the MAM via the MEX process and its implications for other materials./ Design/methodology/approach: This study uses a quantitative approach using robust statistical methods, including Taguchi and Response Surface Methodology designs. Data was collected through a systematic investigation of the effects of process parameters on the physical and mechanical properties of the produced parts. Taguchi’s design was used to determine parameter significance, whereas a Doehlert design was used to optimize responses, focusing on layer adhesion and porosity reduction./ Findings: The results reveal that the optimized extrusion process parameters significantly improved the tensile modulus (198.2±11.9 GPa), tensile strength (977.2±31.8 MPa) and Vickers hardness (287±7 HV100). These findings confirm the efficacy of the methodology, demonstrating that superior mechanical properties can be achieved using desktop equipment. Comparative analysis with professional-grade equipment supports the feasibility of producing cost-effective, high-performance metal parts./ Originality/value: This research offers a novel approach to optimizing MAM via MEX, particularly for stainless steel alloys. The findings contribute valuable insights that extend the current understanding of MEX processes, highlighting the potential for this approach to advance MAM capabilities for industrial applications. This study also identifies areas for future research and potential practical applications, contributing to the broader field of MAM.

Document Type

Article

Document version

Accepted version

Language

English

Pages

p.34

Publisher

Emerald

Published in

Rapid Prototyping Journal 2025, 31 (7), 1362-1382

Grant Agreement Number

info:eu-repo/grantAgreement/MCI/PN I+D/PID2021-123876OB-I00

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Rights

© L'autor/a

© L'autor/a

Attribution-NonCommercial 4.0 International

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IQS [794]