This page consolidates everything that defines us: our direction, mission, vision and values, the manifesto that governs our posture, our team of industrial researchers, and the traceable scientific output that underpins every project. We are an engineering company — and here is the evidence.
To serve and inspire people to build an extraordinary world, driven by technology.
To be our partners' first choice for challenging and meaningful projects.
We are an engineering company.
We don't have ready-made boxes.
We don't sell dreams.
We map constraints.
We respect time.
We work alongside the people on the factory floor, with knowledge and technology — to expressively improve results.
Mekatronik's leadership combines applied industrial research, operations management and technical delivery — the three pillars needed for long-term partnership with large industries.
PhD from UPE, Adjunct Professor and Researcher at the Institute of Technological Innovation (IIT/UPE). Leads Mekatronik's applied industrial research front — 10 peer-reviewed papers, 4 active patents at INPI. Speaker at Hannover Messe 2026, SPS Atlanta 2025, Realize LIVE Americas 2026 and Siemens Mover 2026.
Executive leadership. Coordinates operations and strategic partnerships.
Executive leadership. Coordinates technical deliveries and client relationships with industrial customers.
7 of the 8 professionals work daily at Mekatronik delivering industrial projects. Simultaneously, 6 are enrolled in PhD programs — and the eighth holds a doctorate with a teaching position at UPE. This setup is not accidental. It is the model.
Many digital transformation demands — forecasting gas consumption in a multi-SKU plant, detecting early fatigue in a furnace, automatically adjusting filling dosage — have no ready-made recipe. They are research problems disguised as products. Solving this kind of problem requires scientific method, mastery of the state of the art and the technical honesty to recognize when a route needs to change.
We are not a sales team with an attached researcher. We are a team of researchers who decided to apply scientific method on the shop floor full time. Every project generates documented learning. Every thesis generates an implemented solution. Every patent protects IP that clients are already using.
Real industrial problem → Rigorous scientific research → Implemented solution
↑ ↓
└──────────── Learning → Next problem (more advanced) ←────────────┘
This cycle has produced, over the past 4 years: 10 peer-reviewed publications, 4 active patents at INPI Brazil, 1 software registration (Mksim, 50-year protection), 1 CNPq Research Productivity grant and federal CAPES funding.
Every published paper is verifiable proof of technical competence. Every patent protects IP that clients already use. Nothing we claim is left without a reference.
Q1 journals (Sensors MDPI, IEEE Access) and conferences (SBPO, REPA, ICALT, CBIE) — published in the last 4 years from real industrial client problems.
FDD (fault detection and diagnosis) · FDD with Digital Twin · Industrial Location · Loureiro. Real industrial protection, filed in 2024.
Mksim — registered in 2018, 50-year protection. Industrial simulation software developed by the Mekatronik team.
Hugo Leite · Process 300499/2025-6. Federal recognition of sustained scientific output with documented industrial impact.
From Industry 4.0 and Digital Twin to Deep RL and industrial DataOps. Full coverage of the digital transformation stack — without empty overlap.
CAPES Finance Code 001. The team's projects are co-funded by federal research agencies — alongside industrial clients as co-authors.
Fault detection without ML expertise · real Stellantis Goiana data
AutoML approach enabling industrial engineers — with no machine learning background — to deploy FDD with state-of-the-art results. Published in Sensors (MDPI), a Q1 journal.
FDD with Digital Twin · up to 11 percentage-point improvement in F1
Integration of Digital Twin and machine learning for early fault detection in industrial machines. Published in IEEE Access — open access, verifiable by anyone.
Anomaly detection in float glass · peer-reviewed publication of the Vivix case
Peer-reviewed publication of the Vivix case — real-time refractory monitoring. The same work recognized by Siemens at Realize LIVE Americas 2024.
Food production line · operator reallocation via FlexSim simulation
Discrete modeling of an industrial line and optimization through human-resource reallocation. A 26.45% gain in production rate — with no equipment investment.
Adaptive control of an industrial line via deep reinforcement learning
Application of Deep Reinforcement Learning for dynamic control and optimization of a production line. Research conducted by PhD candidate Rafael Lira (UFPE · Mekatronik).
State of the art in FDD for Industry 4.0 · 29 most relevant works identified
Systematic review of 805 documents — mapping field gaps (XAI, standardised datasets). Scientific foundation of the Mekatronik approach to FDD.
Two PhDs, five MScs in PhD programs and one MSc. All with an active affiliation — at Mekatronik, UPE or UFPE. Seven work on the shop floor daily.
Industrial digital transformation · Digital Twins · FDD · OT/IT integration · Decision support systems
Operations Research · Discrete event simulation · Production system optimisation · Production planning and control
Industrial simulation · Digital Twins · Simulation–automation integration · Operational optimisation applied to manufacturing
Discrete event simulation · Genetic algorithms · Combinatorial optimisation · Line control
Deep Reinforcement Learning · Adaptive production control · AI applied to industry · Operational optimisation
Data mining · Machine learning · Industrial analytics · Complex data processing
Industrial DataOps · Unified Namespace (UNS) · OT/IT architectures · Real-time data pipelines
FDD · Digital Twins · Early fault diagnosis · Industrial computational models
"We are not a sales team with a researcher as an external consultant. We are a team of industrial researchers who decided to apply scientific method on the shop floor — full time."
Dênis Leite · Mekatronik
Every area of expertise is covered by at least one researcher with documented scientific output on the subject. We map the entire digital transformation stack — from strategy to the shop floor.
Federal funding CAPES Finance Code 001. CNPq Research Productivity grant — Hugo Leite, process 300499/2025-6.
When a problem reaches Mekatronik, it goes directly to whoever has the right technical expertise. No intermediary between the industrial problem and the researcher who will solve it. We are based in Recife/PE — an in-person conversation is always more productive, but starting with a call works too.