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Dr. Manuel Arias Chao

Dr. Manuel Arias Chao

Dr. Manuel Arias Chao

ZHAW School of Engineering
Forschungsschwerpunkt Business Engineering and Operations Management
Technikumstrasse 81
8400 Winterthur

+41 (0) 58 934 44 92

Arbeit an der ZHAW

Tätigkeit an der ZHAW

Dozent in Smart Maintenance


Aus- und Weiterbildung

Arbeits- und Forschungsschwerpunkte, Spezialkenntnisse

Machine learning algorithms
Deep learning
Physics informed deep learning
Time series analysis
Fault detection, isolation and prognostics
Predictive & condition-based maintenance

Beruflicher Werdegang

07/2017 - 08/2021 Scientific Assistant on Predictive Maintenance, ETH Zurich
01/2019 - 03/2019 Visiting Scientist, Diagnostics & Prognostics Group, NASA Ames Research Center
07/2017 - 09/2018 Research Associate, Predictive Maintenance, ZHAW
11/2016 - 06/2017 Lead Engineer, Thermo-Economic Optimization, GE Power
11/2015 - 11/2016 Lead Engineer, Gas Turbine Thermodynamics, GE Power
10/2013 - 11/2015 R&D Performance Owner, ALSTOM Power Ltd
10/2008 - 10/2013 R&D Performance Engineer, ALSTOM Power Ltd
07/2006 - 09/2007 Computational Fluid Dynamics (CFD) Engineer, FLUENT France SAS
08/2005 - 06/2006 Aero-engine Maintenance Engineer, Industria de Turbopropulsores S.A

Aus- und Fortbildung

2021 Doctor of Sciences (Dr.sc.), ETH Zurich
2016 CAS in Risk Management for Banking and Finance, University of Zurich
2008 MSc. in Thermal Power, Cranfield University
2005 BSc. in Aeronautical Engineering, Technical University of Madrid



Konferenzbeiträge, peer-reviewed
Weitere Publikationen

Publikationen vor Tätigkeit an der ZHAW

Arias Chao, Manuel, Chetan Kulkarni, Kai Goebel, and Olga Fink (2022). “Fusing physics-based and deep learning models for prognostics”. In: Reliability Engineering & System Safety 217, p. 107961. issn: 0951-8320.

Tian, Yuan, Arias Chao, Manuel, Chetan Kulkarni, Kai Goebel, Olga Fink (2022) “Real-Time Model Calibration with Deep Reinforcement Learning”, In: Mechanical Systems and Signal Processing. 165, p. 108284. issn: 0888-3270.

Arias Chao, Manuel, Bryan T. Adey, and Olga Fink (2021). “Implicit supervision for fault detection and segmentation of emerging fault types with Deep Variational Autoencoders”.
In: Neurocomputing. issn: 0925-2312.

Biggio, Luca, Alexander Wieland, Manuel Arias Chao, Iason Kastanis, and Olga Fink (2021). “Uncertainty-Aware Prognosis via Deep Gaussian Process”. In: IEEE Access 9, pp. 123517–123527.

Arias Chao, Manuel, Chetan Kulkarni, Kai Goebel, and Olga Fink (2021). “Aircraft Engine Run-to-Failure Dataset under Real Flight Conditions for Prognostics and Diagnostics”.
In: Data 6.1, p. 5. issn: 2306-5729.

Unagar, Ajaykumar, Yuan, Tian, Manuel Arias Chao, Olga Fink (2021) “Learning to Calibrate Battery Models in Real-Time with Deep Reinforcement Learning”. In: Energies, 14, 1361.

Arias Chao, Manuel, Chetan Kulkarni, Kai Goebel, and Olga Fink (2019). “Hybrid deep fault detection and isolation: Combining deep neural networks and system performance models”. In: International Journal of Prognostics and Health Management 10, p. 033.

Michau, Gabriel, Manuel Arias Chao, and Olga Fink (2018). "Feature Selecting Hierarchical Neural Network for Industrial System Health Monitoring: Catching Informative Features with LASSO. In: " Proceedings of the Annual Conference of the PHM Society. Vol. 10. No. 1. PHM Society, 2018.

Arias Chao, Manuel, Wippel B, Balmer C, Jakoby R. (2017), "Method for operating a gas turbine plant and gas turbine plant for implementing the method." U.S. Patent No. 9,752,504.

Arias Chao, Manuel, Wilhelm Reiter, and Darrel Shayne Lilley (2017). "Method for operating a power plant." U.S. Patent Application No. 15/241,269.

M. Arias, P. Mathé, et al. (2015) Calibration and Uncertainty Quantification of Gas Turbines Performance Models, ASME paper GT2015-42392

R. C. Payne, M. Arias, V. Stefanis (2014) A Novel Intake Concept for Flue Gas Recirculation to Enhance CCS in an Industrial Gas Turbine, ASME paper GT2014-25469

M. Arias (2013) Calibration and Uncertainty Quantification of Gas Turbines Performance Models, Presentation at Weierstrass Institute for Applied Analysis and Stochastics (WIAS), Seminar Numerische Mathematik, Berlin, June 2013

L. Gallar, M. Arias, V. Pachidis, R. Singh (2011) Stochastic axial compressor variable geometry schedule optimisation, Aerospace Science and Technology, 15 (5) 366-374

L. Gallar, M. Arias, V. Pachidis, P. Pilidis (2009) Compressor Variable Geometry Schedule Optimisation Using Genetic Algorithms, ASME paper GT2009-60049