Shradha Ghansiyal, M.Sc.

Wissenschaftliche Mitarbeiterin

Adresse

Gottlieb-Daimler-Straße
67663 Kaiserslautern

Gebäude 74
Raum 235

Details

  • seit Februar 2022 Wissenschaftlicher Mitarbeiter am FBK
  • Forschungsschwerpunkt: Additive Fertigung

Veröffentlichungen

Zeitschriftenbeiträge

M.M. Müller, S. Ghansiyal, M. Huber, B. Kirsch, M. Glatt, J.C. Aurich: Ein Konzept zur Entwicklung eines wrtschaftlicheren PBF-LB - Steigerung der Wirtschaftlichkeit bei der additiven Fertigung. wt Werkstattstechnik online 113/6 (2023): S.237-241. 0.37544/1436–4980–2023–06–29

L. Yi, J. Mertes, M. Klar, S. Ghansiyal, C. Fei, M. Glatt, J.C. Aurich:A new gradient infill design method for material extrusion using density-based topology optimization and G-code extension. Manufacturing Letters 37 (2023): S.21-25. 10.1016/j.mfglet.2023.06.003

Konferenzbeiträge

S. Ghansiyal, S. Ehmsen, M. Klar, J.C. Aurich: Thermal simulations in additive manufacturing using machine learning. Procedia CIRP 135 (2025): S. 344-349. 10.1016/j.procir.2024.12.029

S. Ghansiyal, M. Schmitz, T. Kirsch, M. Klar, J.C. Aurich: Real-time process monitoring in additive manufacturing using machine learning. Procedia CIRP 134 (2025): S. 79-84. 10.1016/j.procir.2025.03.046

M. Schürmann, S. Varshneya, M. Klar, S. Ghansiyal, M. Kloft, J.C. Aurich: A framework for in-situ process control in metal additive manufacturing using anomaly-driven reinforcement learning. Procedia CIRP 134 (2025): S. 211-216. 10.1016/j.procir.2025.03.050

S. Ghansiyal, L. Yi, M. Klar, J.C. Aurich: Designing Porous Structure with Optimized Topology using Machine Learning. Procedia CIRP 125 Proceedings of the CIRP Conference on Bio Manufacturing (2024): S.190-195 j.procir.2024.08.033

M.M. Müller, S. Ghansiyal, B. Kirsch, M. Glatt, J.C. Aurich: Investigation of the Process Windows of PBF-LB/Ti6Al4V for Variable Laser Spot Diameters. Proceedings of the 23nd Machining Innovations Conference for Aerospace Industry (2023): S. 50-56 10.2139/ssrn.4657776

S. Ghansiyal, L. Yi, P. M. Simon, M. Klar, M. M. Müller, M. Glatt, J.C. Aurich: Anomaly detection towards zero defect manufacturing using generative adversarial networks. Procedia CIRP 120 - Proceedings of the 56th 56th CIRP Conference on Manufacturing Systems (2023): S. 1457-1462. 10.1016/j.procir.2023.09.193

S. Ghansiyal, L. Yi,  J. Steiner-Stark, M.M. Müller, B. Kirsch, M. Glatt, J.C. Aurich: A conceptual framework for layerwise energy prediction in laser-based powder bed fusion process using machine learning. Procedia CIRP 116 - Proceedings of the 30th CIRP Confrence on Life Cycle Engineering (2023): S. 7-12. 10.1016/j.procir.2023.02.002