Timmo Achsel

PhD Researcher

KTH Royal Institute of Technology, Stockholm

• Additive manufacturing & AI in the Department of Production Engineering
• Making additive manufacturing more reliable and industrializable

Project Manager & Topic Owner

OpenResearch GmbH

• Led a hybrid team of 5
• Owned a company-wide topic that set standards for the development lifecycle
• Roadmap owner for a multi-tenant B2B SaaS product, including quality and deployment

Project Manager

MAM Health & Innovation GmbH

• Ran development of patent-pending polymer products
• Launched a patented breastfeeding product
• Led a team of 6 evaluating technical information for patent applications

Electric Product Development Engineer

MAM Health & Innovation GmbH

• Rapid prototyping, functional prototypes and specialised testing rigs
• Patent evaluation and support with patent filings

Trainee R&D Engineer

MAM Health & Innovation GmbH

PhD, Additive Manufacturing & AI

KTH Royal Institute of Technology, Stockholm

BSc Computer Science and Digital Communications

University of Applied Sciences Vienna

MSc High Tech Manufacturing

University of Applied Sciences Vienna

Thesis: Optical sensor-based approach for real-time process monitoring and defect-detection in PBF-LB/P

BSc High Tech Manufacturing

University of Applied Sciences Vienna

Thesis: Development of a Testing Rig for Impact Reduction by MAM Products in Toddlers

Best Master Thesis, 2nd place

Konferenz der Mechatronik Plattform

Master thesis

Additive Manufacturing Science and Education Lab (AMSEL)

Studied heat resistance and failure of photopolymers, then used an additively manufactured housing in a heated build chamber to monitor PBF-LB/P defects with machine learning.

Bachelor thesis

MAM Health & Innovation GmbH

Built a testing rig for impact analysis of falls in toddlers with and without soothers, comparing silicone products on impact reduction in the head and face region.

Your measurements could lie to you by a factor of 3: Multi-objective parameter optimization in LPBF of IN939

Achsel, T., Dileep, D. V., Tomkowski, R., Rashid, A., & Dadbakhsh, S.

Conference paper · Poster · euspen 2026, 26th International Conference & Exhibition, Kraków · kth.diva-portal.org

Optical sensor-based approach for real-time process monitoring and defect-detection in PBF-LB/P

Achsel, T.

Conference paper · Konferenz der Mechatronik Plattform, Wiener Neustadt · mechatronik-plattform.at (PDF)

Best Master Thesis, 2nd place

Real-Time Optical Detection of Artificial Coating Defects in PBF-LB/P Using a Low-Cost Camera Solution and Convolutional Neural Networks

Klamert, V., Achsel, T., Toker, E., Bublin, M., & Otto, A.

Journal article · Applied Sciences 13(20), 11273 · doi:10.3390/app132011273