Curriculum Vitae

Sahil-Jai Arora studied mechanical engineering with a focus on production technology and business management at the RWTH Aachen University. His bachelor's thesis, developed in cooperation with a technology corporation, covers the optimization of existing production systems through smart interlinking and the development of a methodology for performance measurement. The master thesis, which was developed in cooperation with an automotive OEM, deals with the potential assessment, selection, and design of predictive maintenance solutions in manufacturing processes. Furthermore, he was able to gain first professional experience in the fields of automotive engineering, train engineering, and consulting. Since 2020, Mr. Arora is an external PhD student at TU Dortmund University at the ITPL department. His research interests are heating system reliability, reliability prediction, and machine learning methods.



ORCID

0000-0002-6877-1480


Fields of Research



Publications:

Arora, S.-J.; Rabe, M.: Approach to Reference Models for Building Performance Simulation: Establishing a common Understanding. Springer Nature Computer Science 4(2023) article 267. download Details.

Arora, S.-J.: Rabe, M.: Predictive Maintenance: Assessment of Potentials for Residential Heating Systems. International Journal Computer Integrated Manufacturing; 2023, DOI: 10.1080/0951192X.2023.2204471. download Details.

Arora, S.-J.; Weiss, F.; Bräunig, J.; Erkel, S.; Mensing, M.; Wilde, A.: Smarte HeizungsANIaGenOptimierung - ögP SHANGO. Methodik und erste Ergebnisse. In: 32. VDI-Fachtagung Technische Zuverlässigkeit 2023. Nürtingen, April 26th-27th 2023, pp. 24-38.

Arora, S.-J.: Referenzmodell zur Zuverlässigkeitsprognose von Heizsystemen basierend auf Test- und Felddaten. In: Rabe, M.; Scheidler, A.-A. (eds.): Drei Dutzend Jahre Simulationstechnik - Festkolloquium September 2022. Göttingen: Cuvillier 2022, pp. 37-38. download SR_04_Festkolloquium.pdf

Arora, S.-J.; Cecolini; C.; Rabe, M.: Approach to Reference Models for Building Performance Simulation. In: Pires, L.F.; Hammoudi, S.; Seidewitz, E. (eds.): Proceedings of the 10th International Conference on Model-Driven Engineering and Software Development (MODELSWARD) 2022. Virtual Conference, 6th-8th February 2022, pp. 271-278. download Details.

Arora,S.-J.; Ebbecke, C.;Rabe, M.; Fisch. J.: Methodology for the Assessment of Potentials, Selection, and Design of Predictive Maintenance Solutions. Procedia CIRP 104 (2021) 708-713. download Details.


 

Supervised Theses:

Blanke, D.:Systematische Literaturanalyse zu bestehenden Vorgehens- und Referenzmodellen im Bereich Datenanalyse zur Zuverlässigkeitsprognose von Heizsystemen. TU Dortmund University, Department IT in Production and Logistics, bachelor thesis, 2023. download BA_2023_Blanke.pdf

Gerdt, A.: Systematische Literaturanalyse zu bestehenden Vorgehens- und Referenzmodellen zur Zuverlässigkeitsprognose von Heizsystemen. TU Dortmund University, Department IT in Production and Logistics, project thesis, 2023. download FP_2023_Gerdt.pdf

Klein, T.: Systematisierung von Data-Mining-Verfahren in Klassifikatoren und deren prototypische Implementierung und Validierung in RapidMiner. TU Dortmund University, Department IT in Production and Logistics, master thesis, 2022. download MA_2022_Klein.pdf

Klöcker, S. B.: Entscheidungsbaumgestützte Auswahl von Data-Mining-Verfahren im produktionslogistischen Umfeld. TU Dortmund University, Department IT in Production and Logistics, master thesis, 2022. download MA_2022_Kloecker.pdf