Digital and Circular Industrial Services
Focus:
The research group focuses on the initiation, development, and operations of digital and circular industrial services, considering ongoing shifts and issues related to firm and ecosystem levels.
The group positions the research in the context of Industry 4.0/5.0. It will advance knowledge on business model innovation, capability development, and technology infrastructure and architecture in industrial and business-to-business context, considering “user-centered focus”. Our research considers both technological and managerial aspects in exploiting, integrating, and managing the role of different advance digital technologies such as Industrial Internet-of-Things (IIoT), Artificial Intelligence (AI), Cloud Computing, Block Chain, Augmented reality, and Big data analytics in enabling digital and circular industrial services.
With our research, we will contribute to the theories such as digital servitization, business model innovation, smart production/automation, product-service-software systems, and technology integration or industrialization of new technologies.
The research group investigates the relevant topics in following contexts:
- Digital and circular services during product usage or product in operations
- Digital and circular services during the production
- Digital and circular services at the end-of-life
Exploring Dynamic Map Validation at Construction Sites: A Case Study and Feasibility Analysis (Dec 2024) Anas Fattouh, Sara Afshar, Markus Bohlin 27th IEEE International Conference on Intelligent Transportation Systems (ITSC 2024)
DAT (Dec 2024) Ali Asghar Sharifi, Ali Zoljodi , Masoud Daneshtalab Sensors (MDPI Sensors)
TrajectoryNAS (Sep 2024) Ali Asghar Sharifi, Ali Zoljodi , Masoud Daneshtalab Sensors (SENSC9)
Smart Battery Circularity: Towards Achieving Climate-Neutral Electrification (Sep 2024) Koteshwar Chirumalla, Erik Dahlquist, Moris Behnam, Kristian Sandström, Martin Kurdve, Anas Fattouh Advances in Production Management Systems. Production Management Systems for Volatile, Uncertain, Complex, and Ambiguous Environments (AMPS2024)
Contrastive Learning for Lane Detection via cross-similarity (Sep 2024) Ali Zoljodi , Sadegh Abadijou , Mina Alibeigi , Masoud Daneshtalab Pattern Recognition (PR)
A Multilevel Modelling Framework for Quarry Site Operations (Apr 2024) Abdulkarim Habbab, Anas Fattouh, Bobbie Frank , Elianne Lindmark , Koteshwar Chirumalla, Markus Bohlin 12th ACM/IEEE International Workshop on Software Engineering for Systems-of-Systems and Software Ecosystems (SESoS 2024)
Koteshwar Chirumalla, Researcher,Senior Lecturer
Email: koteshwar.chirumalla@mdh.seRoom: L371
Phone: 016-15 32 15