MD Jonaet Ansari
Future Industries Institute
Future Industries Institute
Dr. Md Jonaet Ansari is a Research Associate at the Future Industries Institute, University of Adelaide. He specialises in additive manufacturing, acoustic emission (AE) sensing, defect detection, and advanced materials characterisation.
He completed his PhD in Energy and Advanced Manufacturing at the University of South Australia in 2025, where he developed an innovative acoustic emission (AE)-based monitoring system capable of detecting and quantifying process-induced cracks in components produced using the Directed Energy Deposition (DED) process.
Demonstrating the practical application of his research, Dr. Ansari successfully collaborated with industry partner LaserBond® Ltd to implement an AE-based defect detection system. This initiative utilized advanced signal analysis to enhance process reliability and facilitate early defect detection in a commercial manufacturing environment.
His work integrates experimental validation, signal analysis, and materials performance evaluation to enhance reliability and quality in advanced manufacturing processes. Dr. Ansari is committed to advancing materials science and manufacturing innovation through rigorous research, industry collaboration, and high-impact scholarly publications.
| Year | Citation |
|---|---|
| 2025 | Ansari, M. J., Roccisano, A., Arcondoulis, E. J. G., Schulz, C., Schlafer, T., & Hall, C. (2025). Relationship between associated acoustic emission and crack position during directed energy deposition of a metal matrix composite. Journal of Manufacturing Processes, 147, 177-190. Scopus8 WoS8 |
| 2025 | Dipta, S. D., Rahman, M. M., Ansari, M. J., & Uddin, M. N. (2025). A Comprehensive Review of Sustainable and Green Additive Manufacturing: Technologies, Practices, and Future Directions. Journal of Manufacturing and Materials Processing, 9(8), 52 pages. Scopus10 WoS9 |
| 2025 | Ansari, M. J., Roccisano, A., Arcondoulis, E. J. G., Schulz, C., Schlafer, T., & Hall, C. (2025). Advancements in In-Situ Monitoring Technologies for Detecting Process-Induced Defects in the Directed Energy Deposition Process: a Comprehensive Review. Materials, 18(18, article no.4304), 1-45. Scopus3 WoS3 |
| 2024 | Ansari, M. J., Arcondoulis, E. J. G., Roccisano, A., Schulz, C., Schlaefer, T., & Hall, C. (2024). Optimized analytical approach for the detection of process-induced defects using acoustic emission during directed energy deposition process. Additive Manufacturing, 86(104218), 1-12. Scopus16 WoS16 |
| 2021 | Jonaet, A. M., Park, H. S., & Myung, L. C. (2021). Prediction of residual stress and deformation based on the temperature distribution in 3D-printed parts. International Journal of Advanced Manufacturing Technology, 113(7-8), 2227-2242. Scopus27 WoS27 |
| 2020 | Park, H. S., & Ansari, M. J. (2020). Estimation of residual stress and deformation in selective laser melting of Ti6Al4V alloy. Procedia CIRP, 93, 44-49. Scopus13 WoS10 |
| 2019 | Ansari, M. J., Nguyen, D. S., & Park, H. S. (2019). Investigation of SLM process in terms of temperature distribution and melting pool size: Modeling and experimental approaches. Materials, 12(8), 18 pages. Scopus131 WoS121 Europe PMC16 |
| 2018 | Park, H. S., & Ansari, M. J. (2018). Numerical investigation and an effective predicting system on the Selective Laser Melting (SLM) process with Ti6Al4V alloy. Iop Conference Series Materials Science and Engineering, 400(4), 13 pages. Scopus8 WoS6 |
| Year | Citation |
|---|---|
| 2018 | Park, H. S., Tran, N. H., & Jonaet, A. M. (2018). Prediction of temperature distribution and residual stress in SLM printed parts. In ASME 2018 13th International Manufacturing Science and Engineering Conference Msec 2018 Vol. 1 (pp. 8 pages). TX, Coll Stn: AMER SOC MECHANICAL ENGINEERS. DOI |
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