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Review of quality issues and mitigation strategies for metal powder bed fusion

Jaydeepsinh M. Ravalji (Department of Mechanical Engineering, Faculty of Technology, Dharmsinh Desai University, Nadiad, India)
Shruti J. Raval (Department of Mechanical Engineering, Faculty of Technology, Dharmsinh Desai University, Nadiad, India)

Rapid Prototyping Journal

ISSN: 1355-2546

Article publication date: 28 October 2022

Issue publication date: 4 April 2023

286

Abstract

Purpose

Selective laser melting and electron beam melting processes are well-known for the additive manufacturing of metal parts. Metal powder bed fusion (MPBF) is a common term for them. The MPBF process can empower the manufacturing of intricate shapes by reducing the use of special tools, shortening the supply chain and allowing small batches. However, the MPBF process suffers from many quality issues. In literature, several works are recorded for qualification of the MPBF part. The purpose of this study is to recollect those works done for quality control and report their helpful findings for further research and development.

Design/methodology/approach

A systematic literature review was conducted to highlight the major quality issues in the MPBF process and its root causes. Further, the works reported in the literature for mitigation of these issues are classified and discussed in five categories: experimental investigation, finite element method-based numerical models, physics-based analytical models, in-situ control using artificial intelligence (AI) and machine learning (ML) methods and statistical approaches. A comparison is also prepared among these strategies based on their suitability and limitations. Additionally, improvements in MPBF printers are pointed out to enhance the part quality.

Findings

Analytical models require less computational time to simulate the MPBF process and need a smaller number of experiments to confirm the results. They can be used as an efficient process parameter planning tool to print metal parts for noncritical applications. The AI-ML based quality control is also suitable for MPBF processes as it can control many processing parameters that may affect the quality of the MPBF part. Moreover, capabilities of MPBF printers like thinner layer thickness, smaller beam diameter, multiple lasers and high build temperature range can help in quality control.

Research limitations/implications

This study converts the piecemeal data on MPBF part qualification methods into interesting information and presents it in tabular form under each strategy. This tabular information provides the basis for further quality improvement efforts in the MPBF process.

Originality/value

This study references researchers and practitioners on recent quality control efforts and their significant findings for a better quality of MPBF part.

Keywords

Citation

Ravalji, J.M. and Raval, S.J. (2023), "Review of quality issues and mitigation strategies for metal powder bed fusion", Rapid Prototyping Journal, Vol. 29 No. 4, pp. 792-817. https://doi.org/10.1108/RPJ-01-2022-0008

Publisher

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Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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