[HTML][HTML] In-situ sensing, process monitoring and machine control in Laser Powder Bed Fusion: A review

R McCann, MA Obeidi, C Hughes, É McCarthy… - Additive …, 2021 - Elsevier
Process monitoring and sensing is widely used across many industries for quality
assurance, and for increasing machine uptime and reliability. Though still in the emergent …

A review of the process physics and material screening methods for polymer powder bed fusion additive manufacturing

CA Chatham, TE Long, CB Williams - Progress in Polymer Science, 2019 - Elsevier
Powder bed fusion (PBF) is one of seven different classes of additive manufacturing (AM)
technologies identified by ASTM and ISO. In polymer PBF, an infra-red energy source …

[HTML][HTML] Influence of particle morphology and size distribution on the powder flowability and laser powder bed fusion manufacturability of Ti-6Al-4V alloy

SE Brika, M Letenneur, CA Dion, V Brailovski - Additive Manufacturing, 2020 - Elsevier
Laser powder bed fusion (LPBF) additive manufacturing technology is sensitive to variations
in powder particle morphology and size distribution. However, the absence of a clear link …

Process modeling in laser powder bed fusion towards defect detection and quality control via machine learning: The state-of-the-art and research challenges

P Wang, Y Yang, NS Moghaddam - Journal of Manufacturing Processes, 2022 - Elsevier
In recent years, machine learning (ML) techniques have been extensively investigated to
strengthen the understanding of the complex process dynamics underlying metal additive …

A review on measurement science needs for real-time control of additive manufacturing metal powder bed fusion processes

M Mani, BM Lane, MA Donmez, SC Feng… - International Journal of …, 2017 - Taylor & Francis
Additive manufacturing technologies are increasingly used in the development of new
products. However, variations in part quality in terms of material properties, dimensional …

Review of intelligence for additive and subtractive manufacturing: current status and future prospects

MA Rahman, T Saleh, MP Jahan, C McGarry… - Micromachines, 2023 - mdpi.com
Additive manufacturing (AM), an enabler of Industry 4.0, recently opened limitless
possibilities in various sectors covering personal, industrial, medical, aviation and even …

A framework driven by physics-guided machine learning for process-structure-property causal analytics in additive manufacturing

H Ko, Y Lu, Z Yang, NY Ndiaye, P Witherell - Journal of Manufacturing …, 2023 - Elsevier
Abstract Data analytics with Machine Learning (ML) using physics knowledge and big data
offers high potential to continuously transform raw data to newfound knowledge of Process …

[HTML][HTML] A machine learning guided investigation of quality repeatability in metal laser powder bed fusion additive manufacturing

DJ Huang, H Li - Materials & Design, 2021 - Elsevier
Additive manufacturing has entered the phase of industrial adoption, for which its quality
repeatability is of vital importance to industries where functional parts with consistent …

Feedforward control of thermal history in laser powder bed fusion: Toward physics-based optimization of processing parameters

A Riensche, BD Bevans, Z Smoqi, R Yavari… - Materials & Design, 2022 - Elsevier
We developed and applied a model-driven feedforward control approach to mitigate thermal-
induced flaw formation in laser powder bed fusion (LPBF) additive manufacturing process …

[HTML][HTML] Machine learning-assisted in-situ adaptive strategies for the control of defects and anomalies in metal additive manufacturing

DR Gunasegaram, AS Barnard, MJ Matthews… - Additive …, 2024 - Elsevier
In metal additive manufacturing (AM), the material microstructure and part geometry are
formed incrementally. Consequently, the resulting part could be defect-and anomaly-free if …