ENLYZE
Taline Kehlenbach is a Student Data Scientist at ENLYZE GmbH, where expertise is applied in developing hard- and software solutions to help industrial companies optimize manufacturing quality and profitability through scrap minimization, machine utilization enhancement, and predictive maintenance implementation. Previous experience includes a role as a Student Assistant at Fraunhofer-Institut für Produktionstechnologie IPT, providing support on various industry projects, and another Student Assistant position at RWTH Aachen University. Taline Kehlenbach holds a Master's degree in Data Science from RWTH Aachen University (2020 - 2023) and participated in a student exchange program focused on Artificial Intelligence at Korea Advanced Institute of Science and Technology (March 2022 - December 2022), in addition to earning a Bachelor of Science in Physics from RWTH Aachen University (2016 - 2020).
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ENLYZE
ENLYZE considers industrial power consumption as a universal indicator for predicting the condition of machinery, equipment and manufactured product quality. This approach enables us to realize Predictive Maintenance and Predictive Quality Use Cases from the specially developed current sensor "FLUX". Thus, we create the first universaland scalable implementation of predictive maintenance in the heterogeneous machinery of the manufacturing industry. The FLUX is currently patented and features a non-invasive multiphase power cable measurement methodology (no electrician required for installation). The high-frequency recorded data is then analyzed in the cloud using proprietary AI models.