XPRES - Excellence in Production Research



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The initiative for Excellence in Production Research, XPRES, is a joint initiative between KTH, MDH and Swerea. XPRES was elected as one of two strategic initiatives within Manufacturing engineering in Sweden by the government in 2010. XPRES will establish a long term internationally competitive platform for production research to meet future challenges of world leading Swedish industry. By complementing each others scientific competences and roles, the unique research and education consortium of KTH, MDH and Swerea covers the fields of Production processes, Production systems and Digital engineering. The industrial partners represent world leading Swedish manufacturing industries including: heavy vehicle, machine, component manufacturing and aircraft.

[Show all publications]

Cost-aware Workflow Offloading in Edge-Cloud Computing Using a Genetic Algorithm (Jul 2024)
Somayeh Abdi, Saad Mubeen, Mohammad Ashjaei
The Journal of Supercomputing (Supercomputing)

Towards Compact Surface Languages for Specific Modelling Aspects in EAST-ADL (Jun 2024)
Imad Berrouyne, Alessio Bucaioni, Federico Ciccozzi, Henrik Lönn
12th Embedded Real-Time Systems Congress (ERTS2024)

Continuous Conformance of Software Architectures (Jun 2024)
Alessio Bucaioni, Amleto Di Salle , Ludovico Iovino , Leonardo Mariani , Patrizio Pelliccione
21st IEEE International Conference on Software Architecture (ICSA 2024)

Integrating AIaaS into existing systems: the Gokind experience (Apr 2024)
Benedicte Boneza Musabimana , Alessio Bucaioni
21st International Conference on Information Technology : New Generations (ITNG 2024)

Evolution of an Automotive Modelling Language for Enhanced Support of Diverse Network Interface Controllers (Feb 2024)
Alessio Bucaioni, Saad Mubeen
International Conference on Artificial Intelligence, Control, Data Sciences and Applications 2024 (ACDSA 2024)

Programming with ChatGPT: How far can we go? (Feb 2024)
Vilma Helander , Hampus Ekedahl , Alessio Bucaioni, Thanh Phuong Nguyen
Machine Learning with Applications (MLWA)

KTH Royal Institute of Technology Academic
Swerea IVF Industrial

Jessica Bruch, Professor

Email: jessica.bruch@mdh.se
Room: L328C
Phone: +46 (0)16 153219