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Engineering Science in
Additive Manufacturing Additive manufacturing of EH36 steels

machine learning models, provide continuous feedback The machinability of AMed EH36 steel emerges as a
on key manufacturing parameters using technologies distinct advantage over its conventionally manufactured
such as high-speed imaging, infrared thermography, counterpart, with optimized post-processing techniques
113
112
and in situ cloud processing, enabling early detection of significantly enhancing surface quality and reducing tool
114
anomalies such as thermal distortions, surface defects, and wear. However, challenges, including corrosion resistance,
irregular layer deposition, allowing immediate corrective standardization, and industrial scalability, have yet to be
action and process stability. Furthermore, these machine fully addressed. Future research should prioritize hybrid
learning models can be integrated together into a large-scale manufacturing strategies and in situ repair techniques
framework to iteratively design and optimize AM processes, to enhance cost efficiency and application versatility.
incorporating in situ monitoring for real-time analysis and In addition, integrating advanced technologies such as
defect detection. By leveraging data-driven insights, this machine learning and digital twins can drive process
approach enables continuous improvement in print quality, scanning strategies and process optimization, innovative
process efficiency, and defect mitigation, enhancing the and effective product design, and predictive maintenance,
reliability and performance of printed components. 115,116 reducing the need for endless trial and error and
The collective advancements in numerical simulations, accelerating the adoption of AMed EH36 steel to industrial
digital twin frameworks, and machine learning-driven applications.
optimization are transforming AM process control,
significantly improving the performance, reliability, and Acknowledgments
scalability of AMed EH36 steel components, enabling
broader adoption in marine and offshore engineering where None.
defect-free materials are essential for structural integrity. Funding
8. Conclusion This research was supported by the Manufacturing,
This review provides a comprehensive evaluation of the AM Trade, and Connectivity Programmatic Grant “Advanced
of EH36 steel, highlighting its transformative potential for Models for Additive Manufacturing (AM2)” (grant no.:
marine and offshore applications. It examines key aspects M22L2b0111).
such as process mechanisms, microstructural evolution, Conflict of interest
mechanical properties, machinability, fatigue performance,
and heat treatment strategies. Figure 2 presents a schematic The authors have no conflicts of interest to disclose.
summary illustrating the relationship between different
AM processes and their associated outcomes in terms of Author contributions
microstructure, evaluation methods, and performance Conceptualization: Pan Wang
characteristics. The microstructural section highlights the Project administration: Pan Wang
distinctive features formed in EH36 steel, such as cellular- Supervision: Pan Wang
dendritic grains typical in PBF-LB, acicular ferrite and bainite Visualization: Lin Jie Justin Ang, Jiazhao Huang
structures prominent in DED-LB processes, significant grain Writing – original draft: Lin Jie Justin Ang, Jiazhao Huang
coarsening within the HAZ, and the formation of martensite- Writing – review & editing: All authors
austenite phases. Evaluation methods underscore critical
assessment tools such as density measurements achieving Ethics approval and consent to participate
over 99.5%, detailed microstructural analysis through SEM/
EBSD, phase identification through XRD, and mechanical Not applicable.
performance characterization through tensile and fatigue
tests. The performance aspect emphasizes superior tensile Consent for publication
strength, orientation-dependent toughness, vertical Not applicable.
direction ductility challenges, and the critical management
of residual stresses. Availability of data
This review identifies both the significant progress and Not applicable.
critical challenges in the current state of the field and its
future direction of AMed EH36 steel. Table 5 provides References
a consolidated summary of the critical characteristics, 1. Cagirici M, Guo S, Ding J, Ramamurty U, Wang P. Additive
advantages, and limitations of various AM methods in manufacturing of high-entropy alloys: Current status and
fabricating EH36 steel. challenges. Smart Mater Manuf. 2024;2:100058.

Volume 1 Issue 1 (2025) 12 doi: 10.36922/ESAM025060005