Projects per year
Organisation profile
Organisation profile
At the Department of Mechanical and Manufacturing Engineering, Aalborg University a group of researchers is focused on research in adaptive automation of manufacturing tasks. An adaptive automatic manufacturing system is a system which automatically or semi-automatically can respond to changes in the operating environment.
The mission of the research group is: to create, discover and disseminate knowledge about adaptive automation through research, education, prototype developments and practical implementation.
The vision of the research group is to, within five years, establish frontier research and education facilities within adaptive automation which is ranked among one of the best in Europe.
Motivation
The environment in which most industrial companies are operating is steadily becoming more and more dynamic due to many different conditions (e.g. increased customisation, Smaller and smaller batch sizes, Increased global competition focus on sustainability, technology development).
As a result of this, manufacturing system must be able to cope with an increasing number of variants, to react fast to marked changes, and to have an increased ability to handle the increasing uncertainty associated with the market (market size, competitors, capacity needs, etc).
Existing automatic manufacturing systems are not sufficiently flexible to meet these demands. Normally, they have been developed with a focus on reducing standard unit costs, and improving product quality and ergonomics. These are still very important issues; however, the automatic manufacturing systems of the future must be more adaptive so that they can respond fast and efficient to changes in the operating environment.
It is the development and application of these adaptive systems which is the focus of our research group.
Competences
The competences of the research group are related to advanced automation of manufacturing. Areas covered by the research group are:
- Industrial automation
- robotics
- computer vision
- machine learning
- modelling and control of industrial processes
- sensor based control
- design of advanced manufacturing systems
- digital manufacturing.
Research
The formulated vision is very ambitious and requires research in a large number of areas found in the cross-road between established manufacturing, robotics and automation technologies and emerging technologies in industrial ICT, A.I. cognition, mobile and service robots, autonomous control, and sensing. The huge area cannot be covered by the research group. Instead focus is on a number of selected research objectives and on establishing close collaboration with external partners nationally as well as internationally.
We have selected to focus on:
1. Automation - Making the development process of automatic manufacturing systems more efficient so that:
- systems can be developed faster
- cheaper systems can be developed
- the development can be integrated into the product innovation process.
2. Scalability - Developing systems which fast and efficient can be scaled (in terms of capacity) to meet market demands.
3. Cost/diversity - Making automatic manufacturing systems flexible as well as efficient (goal: standard unit cost independent of volume).
Our Work in Practice
We prioritise that our research is put into practical use. As a result of this most of our research is carried out in close collaboration with industry. This can be end-users and well as system and technology providers.
Furthermore, since it is a characteristic of automation activities in manufacturing that good solutions requires a multi disciplinary approach, we have a great emphasis on establishing close collaboration with research institutions nationally as well as internationally.
We build prototypes (theory guides – but experiments decides)
Finally, we have a focus on maintaining state-of-the-art practical competences in areas as: digital manufacturing, machine vision, Robotics, analysis of manufacturing.
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Collaborations from the last five years
Profiles
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AI:Cybernetics: Efficient human-robot collaboration through artificial intelligence
Chrysostomou, D. (PI), Dideriksen, J. L. (PI), Dosen, S. (Other), Hjorth, C. A. (Project Participant), Malihi, R. N. (Project Participant), Kainat, I. (Project Participant) & Dordevic, P. (Project Participant)
01/08/2025 → 31/07/2028
Project: Research
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REACT: MADE REsilient manufacturing systems through AI-powered and digitally Connected Technologies
Schou, C. (PI), Chrysostomou, D. (Project Participant), Madsen, O. (Project Participant), Andersen, A.-L. (Project Participant), Fibiger, J. (Project Participant), Dzigurski, F. (Project Participant), Acev, D. (Project Participant), Raza, M. (Project Participant) & Michalik, D. (Project Participant)
15/03/2025 → 14/03/2029
Project: Research
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GINP: Robotics collaboration and network between US and Danish universities
Chrysostomou, D. (Project Participant), Nalpantidis, L. (Project Participant), Støy, K. (Project Participant), Zhang, X. (Project Participant), Andersen, O. G. (Project Participant), Nielsen, M. B. (Project Manager), Savarimuthu, T. R. (Project Participant), Schlette, C. (Project Participant), Benaoumeur, S. (Project Participant), Goldberg, K. (Project Participant), Christensen, H. (Project Participant), Gupta, S. K. (Project Participant), Cousins, S. (Project Participant), Singh, H. (Project Participant), Scheel, M. (Project Participant) & Smith, M. (Project Participant)
01/01/2025 → 31/12/2026
Project: Research
Research output
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RAPID Intermodal Transport System: A New Concept for Joint Transportation of Passengers and Freight
Hasslan, S. S., Alieksieiev, V., Shahrivar, R. B., Lange, A.-K., Haavardtun, P. & Steger-Jensen, K., 2026, Advances in Production Management Systems. Cyber-Physical-Human Production Systems: Human-AI Collaboration and Beyond - 44th IFIP WG 5.7 International Conference, APMS 2025, Proceedings. Mizuyama, H., Morinaga, E., Kaihara, T., Nonaka, T., von Cieminski, G. & Romero, D. (eds.). p. 264-278 15 p.Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review
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Shorter and More Agile Supply Chains in Industry 5.0: Case Studies Provide Insights Into Manufacturing Management Theory
Christiansen, A. M., Steger-Jensen, K. & Vidskjold, K., 2026, Advances in Production Management Systems. Cyber-Physical-Human Production Systems: Human-AI Collaboration and Beyond - 44th IFIP WG 5.7 International Conference, APMS 2025, Proceedings. Mizuyama, H., Morinaga, E., Kaihara, T., Nonaka, T., von Cieminski, G. & Romero, D. (eds.). p. 335-348 14 p.Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review
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A Complete System for Automated Semantic–Geometric Mapping of Corrosion in Industrial Environments
Pimentel de Figueiredo, R., Eriksen, S. N., Rodriguez, I. & Bøgh, S., Jun 2025, In: Automation. 6, 2, 28 p., 23.Research output: Contribution to journal › Journal article › Research › peer-review
Open AccessFile21 Downloads (Pure)
Datasets
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"IRWOZ 2.0 - A Large Language Model-driven Dialogue Dataset for Industrial Robot Conversations"
Chen Li (Creator) & Dimitrios Chrysostomou (Creator), IEEE DataPort, 28 Apr 2025
DOI: 10.21227/zpnj-5245
Dataset
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Why Talk to People When You Can Talk to Robots? Far-Field Speaker Identification in the Wild
RO-MAN, 2. 2. (Creator), Chrysostomou, D. (Creator), Humblot-Renaux, G. (Creator) & Li, C. (Creator), Underline Science Inc., 21 Aug 2021
DOI: 10.48448/gae6-9z05, https://underline.io/lecture/30263-why-talk-to-people-when-you-can-talk-to-robotsquestion-far-field-speaker-identification-in-the-wild
Dataset: Supplementary material
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3D point cloud measurements of the surface of HFMI treated and untreated linear butt welds
Mikkelstrup, A. F. (Creator) & Kristiansen, M. (Supervisor), Mendeley Data, 2 Jul 2021
DOI: 10.17632/ktcsh7sykv.1, https://data.mendeley.com/datasets/ktcsh7sykv/1
Dataset
Prizes
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IEEE iSpaRo 2024 Best Paper Runner-up Award
Mortensen, A. B. (Recipient), Pedersen, E. T. (Recipient), Vives Benedicto, L. (Recipient), Burg, L. (Recipient), Madsen, M. R. (Recipient) & Bøgh, S. (Recipient), 26 Jun 2024
Prize: Conference prizes
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Activities
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Intelligent Anomaly Detection in Manufacturing A Multi-Sensor ML Approach to Predictive Maintenance
LI, C. (Lecturer)
13 Nov 2025Activity: Talks and presentations › Talks and presentations in private or public companies
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International Journal of Human-Computer Interaction (Journal)
Chrysostomou, D. (Peer reviewer)
1 Sept 2025 → …Activity: Editorial work and peer review › Peer review of manuscripts › Research
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Conversational AI for industrial robots in manufacturing settings
LI, C. (Speaker)
26 Aug 2025Activity: Talks and presentations › Talks and presentations in private or public companies
Press/Media
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AI gør danske virksomheder markant mere effektive
11/12/2025
1 item of Media coverage
Press/Media: Press / Media
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AI minimerer fejl og forlænger værktøjets levetid i produktionen
25/11/2025
1 item of Media coverage
Press/Media: Press / Media
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Frederikshavn Havn har potentiale til at blive en stærk og bæredygtig virksomhed
12/11/2025
1 item of Media coverage
Press/Media: Press / Media
Impacts
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A method for processing elements into final elements
Kristiansen, M. (Participant), Endelt, B. (Participant), Thomsen, A. N. (Participant) & Mikkelstrup, A. F. (Participant)
Impact: Economic impact
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A planning method for processing an element into a final element
Kristiansen, M. (Participant), Endelt, B. (Participant), Thomsen, A. N. (Participant), Mikkelstrup, A. F. (Participant) & Nikolov, G. (Participant)
Impact: Economic impact
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Scanning Robot for Pregnant Women Reduces Strain on Staff
Chrysostomou, D. (Participant), Madsen, O. (Participant), Hjorth, S. (Participant), Kristensen, R. (Participant), Pedersen, B. K. (Participant) & Størup, G. (Participant)
Impact: Quality of life impact, Economic impact
Facilities
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5G Smart Production Lab
Schou, C. (Manager) & Larrad, I. R. (Manager)
Department of Materials and ProductionFacility: Laboratory