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School of Industrial Engineering and Management

Our core knowledge areas include industrial design and innovation, product and production development, materials development, energy technology, learning in engineering sciences as well as industrial economics, organisation and management. Our efforts are directed towards a green and sustainable society for the future.

Departments 

Competence Centers

Center for Mechanics and Materials Design (MMD) Center for X-rays in Swedish materials science (CeXS) Centre of Excellence in Production Research (XPRES) Design & Management of Manufacturing Systems (DMMS)
Dig-IT Lab Integrated Transport Research Lab (ITRL) Innovative Centre for Embedded Systems (ICES) KTH Climate Action Centre
Lean Center KTH Live-In Lab Neutron and X-ray science for industrial technology transitions (NEXT) Trustworthy Edge Computing Systems and Applications (TECoSA)

Latest news

Henrik Sieurin.
Henrik Sieurin is new adjunct professor at the Department of Materials Science.

Advancing collaboration for advanced high-strength steels

Henrik Sieurin earned his PhD at KTH. Now he’s back as an adjunct professor and expert in fatigue of the world’s most recycled material – steel. With a focus on collaboration for smarter solutions in ...

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Man and woman in KTHB
President Anders Söderholm and centre director Pia Höök at the launch of Inspirelab. Photo: Anna Gullers

New centre puts equality at the heart of tech

Gender equality will now be safeguarded in technical innovations. On Monday, InspireLab was inaugurated - a new center at KTH dedicated to promoting gender equality through technology and innovation.

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KTH building Digital Futures
The symposium takes place at Digital Futures on 16–19 September, 2025.

Singapore and KTH join forces on AI

AI is reshaping how we work and learn – but how do we build inclusive and future-proof knowledge? On September 16–18, KTH/Digital Futures, Örebro University and Linköping University are bringing toget...

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Calendar

More events at the ITM School

Publications

[1]
M. Sun et al., "Out-of-order execution enabled deep reinforcement learning for dynamic additive manufacturing scheduling," Robotics and Computer-Integrated Manufacturing, vol. 91, 2025.
[2]
Y. Qin et al., "A tool wear monitoring method based on data-driven and physical output," Robotics and Computer-Integrated Manufacturing, vol. 91, 2025.
[3]
D. Sharma et al., "Electrochemicaland computational insightsinto the utilization of an N-heteroaromatic containing compound2-(4-Methoxy-phenyl)-5-naphthalen-2-yl-[1,3,4]oxadiazole as a promising anticorrosive agent for mild steel in corrosive medium," Journal of Molecular Structure, vol. 1321, 2025.
Full list in the KTH publications portal