Ramón van Dooren

Electromechanical engineer, ir.

I design, simulate and build electromechanical systems, and I write the software that runs them.

Ramón van Dooren

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Abstract

Who is Ramón van Dooren?

Title
ir., MSc
Field
Electromechanical engineering
Specialisation
Design and Production
Based in
Limburg, the Netherlands
Languages
Dutch, English

Ramón van Dooren is an electromechanical engineer (ir., MSc) based in Limburg, the Netherlands, working in mechatronics and mechanical design. He holds a Master of Science in Electromechanical Engineering Technology, specialisation Design and Production, a joint degree of Hasselt University and KU Leuven, awarded with great distinction in 2025, and a Bachelor of Science in the same field, awarded with distinction in 2024. His work covers the whole engineering loop: measurement and machine vision, electromagnetic and thermal simulation in COMSOL Multiphysics, mechanical design in Creo Parametric and Siemens NX with GD&T, CNC and CAM production, and control software in Python. His master’s thesis at IUMAT (UHasselt and imec) concerned a liquid metal deposition tool for magnetic direct writing of stretchable electronics. He also founded Ravando, where he engineers self-correcting AI systems.

Keywords: mechatronics, mechanical design, computational electromagnetics, heat transfer, finite element method, GD&T, CNC and CAM, machine vision, control systems, Python.

Method

Capabilities

Four stages of one loop. Each one feeds the next, and the last feeds the first.

01

Perceive

Measure before deciding.

Every design starts with what the system really does. I define the requirements, choose the sensors and the measuring method, and turn raw signals and images into numbers a design can rest on.

  • Measurement systems
  • Dimensional metrology
  • Machine vision in MVTec HALCON
  • Sensor technology
  • Requirements analysis
uc2(y)=∑i=1N(∂f∂xi)2u2(xi)u_c^{2}(y)=\sum_{i=1}^{N}\left(\frac{\partial f}{\partial x_i}\right)^{2}u^{2}(x_i)
(1)
Combined standard uncertainty of a result y=f(x1,…,xN)y=f(x_1,\dots,x_N) with uncorrelated inputs.

02

Reason

Model it before building it.

I work a design out by hand first, then check it numerically. That means electromagnetic and thermal simulation in COMSOL Multiphysics, finite element analysis, vibration analysis and systematic materials selection.

  • Computational electromagnetics
  • Heat transfer
  • Finite element method
  • Vibrations
  • Materials selection in GRANTA EduPack
∇×(μ−1 ∇×A)=J,B=∇×A\nabla\times\left(\mu^{-1}\,\nabla\times\mathbf{A}\right)=\mathbf{J},\qquad\mathbf{B}=\nabla\times\mathbf{A}
(2)
Magnetostatics in vector potential form, the equation behind a coil and core simulation.
ρ cp ∂T∂t=∇⋅(k ∇T)+Q\rho\,c_p\,\frac{\partial T}{\partial t}=\nabla\cdot\left(k\,\nabla T\right)+Q
(3)
Heat conduction with a volumetric source QQ, such as resistive loss in a winding.

03

Act

Turn the model into hardware.

I take a concept through CAD to a complete production dossier: 3D design in Creo Parametric and Siemens NX, drawings with geometric dimensioning and tolerancing, component selection, and CNC and CAM programming down to the G-code.

  • Creo Parametric
  • Siemens NX
  • GD&T
  • CNC and CAM
  • G-code
  • Electric drives and robotics
L10=(CP)pL_{10}=\left(\frac{C}{P}\right)^{p}
(4)
Basic rating life of a rolling bearing in millions of revolutions (ISO 281), with p=3p=3 for ball and p=10/3p=10/3 for roller bearings.
M=E1/2ρM=\frac{E^{1/2}}{\rho}
(5)
Material index to maximise for a light, stiff column loaded in compression.

04

Learn

Close the loop.

A system is finished when the measured result matches the model. I verify the build against the design, feed the difference back in, and write the control and automation software. That includes feedback control and AI pipelines that detect and correct their own errors.

  • Feedback and control systems
  • Verification and testing
  • Python
  • Agentic AI workflows
T(s)=C(s) G(s)1+C(s) G(s)T(s)=\frac{C(s)\,G(s)}{1+C(s)\,G(s)}
(6)
Closed-loop transfer function of a plant GG under a controller CC with unity feedback.

Record

Education and record

Table 1. Academic and professional record.
YearEntryInstitution
Education
2026Dutch engineering title ir. (ingenieur)Granted by DUO, the Netherlands
2025MSc Electromechanical Engineering Technology, specialisation Design and Production. Great distinction.Hasselt University and KU Leuven, joint degree
2025Erasmus+ Blended Intensive Programme: Digital and Sustainable Transition in the Automotive IndustryFree University of Bozen-Bolzano
2024BSc Electromechanical Engineering Technology. Distinction.Hasselt University and KU Leuven
Thesis projects
MScDesign and development of a liquid metal deposition tool for magnetic direct writing. The engineering process, including simulation, production and verification, of a magnetically assisted manufacturing system for research into stretchable electronic devices such as soft robotics and healthcare sensors.IUMAT (UHasselt and imec)
BScAutomated discharge and buffer system for robotically harvested apples. Complete mechanical design and production dossier, including GD&T.ACRO (KU Leuven) with pcfruit vzw
Experience
NowAI systems engineer and founder. Engineering self-correcting agentic AI pipelines and workflows that automate revenue operations and core internal business operations.Ravando, Sittard
NowTechnical co-founder. Product and web design, automations, and AI workflow integration.Beyond Olympus
Languages
Dutch (native), English (full professional), German and French (basic)

Questions

Questions and answers

What does Ramón van Dooren do?

Ramón van Dooren is an electromechanical engineer (ir., MSc) who works in mechatronics and mechanical design. He measures, simulates, designs and builds physical systems, and he writes the control and automation software around them.

What did Ramón van Dooren study?

He holds an MSc in Electromechanical Engineering Technology, specialisation Design and Production, a joint degree of Hasselt University and KU Leuven, awarded with great distinction in 2025. His BSc in the same field was awarded with distinction in 2024.

Which engineering tools does he use?

Creo Parametric and Siemens NX for design, COMSOL Multiphysics for electromagnetic and thermal simulation, GD&T for drawings, CNC and CAM with G-code for production, MVTec HALCON for machine vision, GRANTA EduPack for materials selection, and Python.

What was his master’s thesis about?

The design and development of a liquid metal deposition tool for magnetic direct writing, carried out at IUMAT (UHasselt and imec) for research into stretchable electronics. The research is still running, so the details are not published here.

What is Ravando?

Ravando is the company Ramón van Dooren founded. There he engineers self-correcting agentic AI pipelines and workflows that automate revenue operations and internal business operations.

How can I reach Ramón van Dooren?

By email at contact@ramonvandooren.com, or through LinkedIn at linkedin.com/in/ramonvandooren.