Álvaro Obregón, Mexico City, Mexico
I work at the intersection of Digital Manufacturing, Industrial AI, and Data Science, focusing on designing and deploying Digital Twin–driven production systems. My core objective is simple: → turn manufacturing data into operational decisions that improve cost, throughput, and reliability I bring a hybrid profile combining: • Engineering depth (manufacturing systems, automation, control) • Data science capabilities (machine learning, Bayesian methods, optimization) • System integration (IIoT, simulation, and real production environments) Over the past 15+ years, I have: • Developed and optimized manufacturing and automation systems in both industry and academia • Worked as a Systems Engineer at Roche, focusing on product modeling and process improvement (Six Sigma) • Conducted research at RWTH Aachen in machine tools and production systems • Leading the Industrial Engineering Department at ITAM, building programs in Digital Manufacturing and Industry 4.0 Currently, I am completing a Master’s in Data Science, strengthening my expertise in: • Machine learning for industrial applications • Bayesian modeling and uncertainty quantification • Data-driven optimization of complex systems What differentiates my work is the integration of: → physics-based models + machine learning + operational decision systems This allows moving beyond dashboards into true Digital Twin environments capable of prediction, simulation, and optimization. I am particularly interested in: • Digital Manufacturing & Smart Factories • Industrial AI applications • Scalable Digital Twin architectures • Data-driven operations and supply chains Open to collaboration and roles where engineering, data, and business impact intersect.
- Leading the strategic development of Digital Manufacturing and Industry 4.0 initiatives - Developing data-driven manufacturing frameworks combining simulation, optimization, and machine learning - Managing cross-functional teams across engineering, data, and operations domains - Built industry-aligned programs focused on automation, robotics, and industrial analytics (see Projects section: Digital Twin Learning Factory) (see Projects section: Manufacturing Analytics Model)
- Transformed curriculum towards Digital Manufacturing, IIoT, and Data Science integration - Introduced Digital Twin and Smart Factory concepts into engineering education - Led program growth, industry partnerships, and student placement strategies
Administrative Responsibilities: Coordination of Laboratory - Renovation and modernization of equipment - License management - Maintenance of equipment - Scheduling - Contractor management Lectures: - Kinematic / Kinetic Analysis and Synthesis - Computer Integrated Manufacturing - Mechatronic Systems - Mechanics of Solids Research and Investigation: - Industry 4.0 with a focus on Cyber-Physical Systems - Systems Engineering and Computer-Aided Engineering
- Control Theory and Control Engineering - Automation of Manufacturing Systems - Mechatronic Design
- Design of Mechatronic Systems based in the DFSS methology - Systems simulation and systems dimensioning - Evaluation and analysis of production data using Six Sigma Tools - Computed Aided Manufacturing and optimization of G-Code
- Developed model-based systems for medical devices (insulin delivery systems) - Applied Six Sigma methodologies to improve product performance and processes - Worked on system modeling, validation, and optimization