Relab – USP Reliability Laboratory

RESEARCH AND INNOVATION IN RELIABILITY

The Reliability Laboratory (Relab) at the University of São Paulo is a research center dedicated to developing advanced solutions for challenges related to the reliability and maintenance of industrial systems. Our laboratory works in areas such as maintenance management, fault detection and diagnosis, prognosis, and reliability-based design. We connect academic research and real industry demands to create innovations that positively impact the productive sector and society.

LINES OF RESEARCH

Maintenance
Management

Solutions to optimize maintenance strategies, reducing costs and maximizing the availability of industrial systems

AI-supported Predictive Maintenance

Using artificial intelligence techniques to predict failures, increase operational efficiency and avoid unplanned downtime

Reliability-Based Design

Development of systems designed for high performance and durability, aligned with the demands of modern industry

RELAB IN NUMBERS

Active Researchers

212

Publications

Projects with Partner Companies

Graduated Masters

Graduated Doctors

135

Participation in Congresses

PROFESSORS

Full Professor at the Department of Mechatronic Engineering and Mechanical Systems at the Polytechnic School of USP and Founder of Relab. His research covers reliability-based design and structural reliability, using artificial intelligence to improve the performance and safety of complex systems.

Assistant Professor at the Department of Mechatronic Engineering and Mechanical Systems of the Polytechnic School of USP. Researcher dedicated to the development of innovative solutions in reliability and maintenance, with a focus on the use of artificial intelligence for diagnosis, failure prognosis and optimization of industrial systems.

Assistant Professor at the Production Department of the Polytechnic School of USP. He develops research in maintenance management and asset management, applying artificial intelligence to optimize maintenance strategies and increase operational efficiency.

Temporary Professor at the Department of Production Engineering of the Polytechnic School of USP. His research focuses on fault detection in rotating machines, using artificial intelligence to predict faults and improve the reliability of industrial equipment.