Biography:
Dr. Miguel A. Sanz-Bobi is working in IIT since 1985 and has been involved in more than twenty research projects for the industry, mainly for the electrical industryHis main research activities are related with applications to the reliability and maintainability field and the development of expert systems and use of artificial intelligence techniques for on-line diagnosis of incipient problems in large industrial processes such as power plants, machine tools, etc.He obtained the Degree of Doctor in 1992 from the Universidad Politécnica de Madrid, Madrid, Spain. His doctoral thesis described a methodology for predictive maintenance based on the health condition of equipments of complex industrial processes.
Areas of interest:
Life condition monitoring and analysis of industrial processes. Modeling and simulation of the expected behavior of industrial components. Artificial Intelligence: knowledge-based systems, fuzzy logic, machine learning algorithms, reinforcement learning. Techniques for incipient detection of failure modes and risk assessment. Reliability. Predictive Maintenance. Asset Management. Image and voice treatment.
Skills:
Symbolic AI: Expert systems Decision trees Case-based reasoning Fuzzy logic Machine learning: Unsupervised machine learning: Clustering Supervised machine learning: neural networks, random forests, gradient booster… Reinforcement learning Generative AI: Generative Adversarial Networks Image, video, audio processing Evaluation of the condition of industrial processes. Predictive maintenance models. Methods characterizing the normal behavior expected in industrial systems and asset management
F.J. Bellido-López, M.A. Sanz-Bobi, A. Muñoz, D. González-Calvo, T. Álvarez Tejedor, "A novel method for evaluation of the maintenance impact in the health of industrial components", Results in Engineering, Vol. 27, pp. 105809, September 2025. [Online: June 2025] doi: 10.1016/j.rineng.2025.105809
C. Domínguez-Barbero, J. García-González, M.A. Sanz-Bobi, A. García-Cerrada, "Energy management of a microgrid considering nonlinear losses in batteries through Deep Reinforcement Learning", Applied Energy, Vol. 368, pp. 123435, August 2024. [Online: May 2024] doi: 10.1016/j.apenergy.2024.123435
C. Domínguez-Barbero, J. García-González, M.A. Sanz-Bobi, "Twin-delayed deep deterministic policy gradient algorithm for the energy management of microgrids", Engineering Applications of Artificial Intelligence, Vol. 125, pp. 106693, October 2023. [Online: July 2023] doi: 10.1016/j.engappai.2023.106693
P. Calvo-Báscones, A. Voisin, P. Do, M.A. Sanz-Bobi, "A collaborative network of digital twins for anomaly detection applications of complex systems. Snitch Digital Twin concept", Computers in Industry, Vol. 144, pp. 103767, January 2023. [Online: September 2022] doi: 10.1016/j.compind.2022.103767
M.C. Rubiales Mena, A. Muñoz, M.A. Sanz-Bobi, D. González-Calvo, T. Álvarez Tejedor, "Time Series-Based Anomaly Detection in Gas Turbines Using TimeWGAN-GP", IEEE Access, Vol. 14, pp. 113355 - 113377, 2026. [Online: July 2026] doi: 10.1109/ACCESS.2026.3715914
G.L. Rajora, M.A. Sanz-Bobi, L. Bertling Tjemberg, P. Calvo-Báscones, "Refining Open-Source Asset Management Tools: AI-Driven Innovations for Enhanced Reliability and Resilience of Power Systems", Technologies, Vol. 14, nº. 1, pp. 57, January 2026. [Online: January 2026] doi: 10.3390/technologies14010057
G.L. Rajora, M.A. Sanz-Bobi, C. Mateo, L. Bertling Tjemberg, "An Open-Source Tool-Box for Asset Management based on the asset condition for the Power System", IEEE Access, Vol. 13, pp. 49174 - 49186, 2025. [Online: March 2025] doi: 10.1109/ACCESS.2025.3551663
M.A. Sanz-Bobi, I. Rodríguez-Muñoz-de-Baena, F.J. Bellido-López, A. Muñoz, J. Anguera, D. González-Calvo, T. Álvarez Tejedor, "TD3 Reinforcement Learning Algorithm Used for Health Condition Monitoring of a Cooling Water Pump", Computers, Vol. 14, nº. 12, pp. 540, December 2025. [Online: December 2025] doi: 10.3390/computers14120540
F.J. Bellido-López, M.A. Sanz-Bobi, A. Muñoz, D. González-Calvo, T. Álvarez Tejedor, "Maintenance-Aware Risk Curves: Correcting Degradation Models with Intervention Effectiveness", Applied Sciences, Vol. 15, nº. 20, pp. 10998, October 2025. [Online: October 2025] doi: 10.3390/app152010998
F.J. Bellido-López, M.A. Sanz-Bobi, A. Muñoz, D. González-Calvo, T. Álvarez Tejedor, "A novel method for evaluation of the maintenance impact in the health of industrial components", Results in Engineering, Vol. 27, pp. 105809, September 2025. [Online: June 2025] doi: 10.1016/j.rineng.2025.105809
M. Casero, M.A. Sanz-Bobi, F.J. Bellido-López, A. Muñoz, D. González-Calvo, T. Álvarez Tejedor, "Efficiency monitoring of a cooling water pump based on machine learning techniques", International Journal of Prognostics and Health Management, Vol. 16, nº. 1, pp. 1 - 6, December 2024. [Online: January 2025] doi: 10.36001/ijphm.2025.v16i1.4160
C. Domínguez-Barbero, J. García-González, M.A. Sanz-Bobi, A. García-Cerrada, "Energy management of a microgrid considering nonlinear losses in batteries through Deep Reinforcement Learning", Applied Energy, Vol. 368, pp. 123435, August 2024. [Online: May 2024] doi: 10.1016/j.apenergy.2024.123435
G.L. Rajora, M.A. Sanz-Bobi, L. Bertling Tjemberg, J.E. Urrea Cabus, "A review of asset management using artificial intelligence-based machine learning models: applications for the electric power and energy system", IET Generation, Transmission & Distribution, Vol. 18, nº. 12, pp. 2155 - 2170, June 2024. [Online: June 2024] doi: 10.1049/gtd2.13183
C. Domínguez-Barbero, J. García-González, M.A. Sanz-Bobi, "Twin-delayed deep deterministic policy gradient algorithm for the energy management of microgrids", Engineering Applications of Artificial Intelligence, Vol. 125, pp. 106693, October 2023. [Online: July 2023] doi: 10.1016/j.engappai.2023.106693
H. de Santos Yubero, M.A. Sanz-Bobi, "A machine learning approach for condition monitoring of high voltage insulators in polluted environments", Electric Power Systems Research, Vol. 220, pp. 109340, July 2023. [Online: March 2023] doi: 10.1016/j.epsr.2023.109340
P. Calvo-Báscones, A. Voisin, P. Do, M.A. Sanz-Bobi, "A collaborative network of digital twins for anomaly detection applications of complex systems. Snitch Digital Twin concept", Computers in Industry, Vol. 144, pp. 103767, January 2023. [Online: September 2022] doi: 10.1016/j.compind.2022.103767
P. Calvo-Báscones, M.A. Sanz-Bobi, "Advanced prognosis methodology based on behavioral indicators and chained sequential memory neural networks with a diesel engine applicat", Computers in Industry, Vol. 144, pp. 103771, January 2023. [Online: September 2022] doi: 10.1016/j.compind.2022.103771
I. Álvarez-Monteserín, M.A. Sanz-Bobi, "An online fade capacity estimation of lithium-ion battery using a new health indicator based only on a short period of the charging voltage profile", IEEE Access, Vol. 10, pp. 1138 - 11146, 2022. [Online: January 2022] doi: 10.1109/ACCESS.2022.3143107
W.C.E. Teixeira, M.A. Sanz-Bobi, R.C. Limão Oliveira, "Applying intelligent multi-agents to reduce false alarms in wind turbine monitoring systems", Energies, Vol. 15, nº. 19, pp. 7317, October 2022. [Online: October 2022] doi: 10.3390/en15197317
H. de Santos Yubero, M.A. Sanz-Bobi, "Research on the pollution performance and degradation of superhydrophobic nano-coatings for toughened glass insulators", Electric Power Systems Research, Vol. 191, pp. 106863, February 2021. [Online: October 2020] doi: 10.1016/j.epsr.2020.106863
C. Domínguez-Barbero, J. García-González, M.A. Sanz-Bobi, E.F. Sánchez-Úbeda, "Optimising a microgrid system by deep reinforcement learning techniques", Energies, Vol. 13, nº. 11, pp. 2830, June 2020. [Online: June 2020] doi: 10.3390/en13112830
A. Gil, M.A. Sanz-Bobi, M.A. Rodríguez López, "Behavior anomaly indicators based on reference patterns - application to the gearbox and electrical generator of a wind turbine", Energies, Vol. 11, nº. 1, pp. 87, January 2018. [Online: January 2018] doi: 10.3390/en11010087
P. Mazidi, Y. Tohidi, M.A. Sanz-Bobi, "Strategic maintenance scheduling of an offshore wind farm in a deregulated power system", Energies, Vol. 10, nº. 3, pp. 313, March 2017. [Online: March 2017] doi: 10.3390/en10030313
M.A. Sanz-Bobi, T. Welte, L. Eilertsen, "Anomaly indicators for Kaplan turbine components based on patterns of normal behavior", presented at 28th European Safety and Reliability Conference - ESREL 2018, Trondheim, Norway, 17-21 June 2018. In: Safety and Reliability – Safe Societies in a Changing World: Proceedings of ESREL 2018 , June 17-21, 2018, Trondheim, Norway, pp. 1003-1010, doi: 10.1201/9781351174664-126
M.A. Sanz-Bobi, A. Muñoz, A. de Marcos, M. Bada, "Intelligent system for a remote diagnosis of a photovoltaic solar power plant", presented at 25th International Congress on Condition Monitoring and Diagnostics Engineering Management - COMADEM 2012, Huddersfield, United Kingdom, 18-20 June 2012. In: Journal of Physics: Conference Series, vol. 364, pp. 012119-1/012119-12, doi: 10.1088/1742-6596/364/1/012119
R. Martínez, M.A. Sanz-Bobi, "Divisible rough sets based on self-organizing maps", presented at 1st International Conference on Pattern Recognition and Machine Intelligence - PReMI 2005, Kolkata, India, 20-22 December 2005. In: Pattern Recognition and Machine Intelligence: Proceedings of the 1st International Conference on Pattern Recognition and Machine Intelligence - PReMI 2005, pp. 708-713, doi: 10.1007/11590316_114
M. Gržanić, K. Šepetanc, M.F. Simões, F.J. Soares, A. Churkin, E. Martines Cesena, B. Mohandes, F. Capitanescu, M.I. Alizadeh, M.A. Sanz-Bobi, C. Mateo, T. Gibon, S. Bednarova, "Tools test and validation results". Project: ATTEST / WP7 / D7.2. Funded by Comisión Europea whitin "Horizon 2020 – Cooperation / Energy". Oct/2023. IIT-23-457I
C. Bagnasco, C. Biasuzzi, K. Hakan, F. Capitanescu, M. Bolfek, D. Mešić, E. Martines Cesena, M.A. Sanz-Bobi, M.F. Simões, J. Rodrigues, M. Gržanić, T. Capuder, D. Vrbicic Tendera, P. Sagrestano Stamuk, H. Keko, "Toolbox specification". Project: ATTEST / WP2 / D2.2. Funded by Comisión Europea whitin "Horizon 2020 – Cooperation / Energy". Sep/2020. IIT-20-281I