Dr. Hatem Algabroun is a senior lecturer/assistant professor in the Department of Mechanical Engineering at Linnaeus University. He earned his PhD in Mechanical Engineering from Linnaeus University in 2020, with a focus on maintenance engineering and industrial digitalization. His research addresses the intersection of smart maintenance, predictive maintenance, and industrial digitalization and automation, with the goal of improving reliability and efficiency in manufacturing environments.
Teaching
Dr. Algabroun teaches across all levels of higher education, including bachelor, master, and doctoral programmes. At the bachelor’s level, he has taught courses such as Programmering i MATLAB (1MT032), Reliability and Maintenance Technology (1MT331), Facility Planning (2MT029), and Thesis in Industrial Engineering (2MT14E). He currently teaches Material Planning and Production Control I (1MT020), as well as Research Methods and Opposition (2MT345). At the master’s level, he teaches Condition Monitoring and Predictive Maintenance (4MT081), and he is also involved in the doctoral-level course titled Swedish Perspectives on Maintenance Research: Past, Present, and Future (5 hp).
Research
His primary research interests lie in predictive maintenance and condition monitoring, adaptive sampling strategies, smart maintenance systems, and the broader digitalization of industrial processes. Dr. Algabroun has been actively involved in externally funded research initiatives that support the automation and digital transformation of the manufacturing sector, particularly small and medium-sized enterprises (SMEs). He has contributed to and taken leadership roles in projects funded by bodies such as the EU, ERDF, and the Knowledge Foundation. His work often involves collaboration with industry partners and includes both applied research and the development of professional education in the areas of smart maintenance and industrial digitalization.
My research groups
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Mechanical Engineering The research in the field of mechanical engineering is broad and has its main focus in six areas: structural dynamics, material science, industrial economics, terotechnology,…
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Smart Industry Group Smart Industry Group (SIG) is an interdisciplinary research group featuring expertise from computer science and mechanical engineering. SIG's focus is making production and…
My ongoing research projects
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Project expert competence: Smart Industry, phase 2 The goal of the project is to develop courses at advanced level linked to Smart Industry based on the skills needs of industry. The project's target…
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Project: Smart Dat The goal of the project is to offer activities in automation and digitalization for small and medium-sized companies in the manufacturing sector in the Linnaeus region, strengthen…
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Seed project: Machine learning for predicting the mechanical properties of high performance oxynitride glasses This project aims to develop a machine learning (ML) model to predict the mechanical…
My completed research projects
Publications
Article in journal (Refereed)
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Nuttah, M.M., Algabroun, H., Linhares, C.D.G., Håkansson, L. (2025). Creative Destruction and Technological Paradigms in Manufacturing : A Large-Scale Review and Framework for Technology Portfolio Assessment. IEEE transactions on engineering management. 72. 3397-3418.
Status: Published -
Algabroun, H., Håkansson, L. (2025). Parametric Machine Learning-Based Adaptive Sampling Algorithm for Efficient IoT Data Collection in Environmental Monitoring. Journal of Network and Systems Management. 33 (1).
Status: Published -
Algabroun, H., Bokrantz, J., Al-Najjar, B., Skoogh, A. (2022). Development of digitalised maintenance : a concept. Journal of Quality in Maintenance Engineering. 28 (2). 367-390.
Status: Published -
Algabroun, H. (2020). Dynamic sampling rate algorithm (DSRA) implemented in self-adaptive software architecture : a way to reduce the energy consumption of wireless sensors through event-based sampling. Microsystem Technologies : Micro- and Nanosystems Information Storage and Processing Systems. 26 (4). 1067-1074.
Status: Published -
Algabroun, H., Iftikhar, M.U., Al-Najjar, B., Weyns, D. (2018). Maintenance 4.0 Framework using Self : Adaptive Software Architecture. Journal of Maintenance Engineering. 2. 280-293.
Status: Published -
Al-Najjar, B., Algabroun, H., Jonsson, M. (2018). Maintenance 4.0 to fulfil the demands of Industry 4.0 and Factory of the Future. International Journal of Engineering Research and Applications. 8 (11). 20-31.
Status: Published
Conference paper (Refereed)
- Ainin, A., Algabroun, H., Linhares, C.D.G. (2025). Augmented Reality for Training in Small and Medium-Sized Manufacturing Companies. .
- Ziada, O., Zhang, Y., Algabroun, H., Abiri, O., Olaogun, O., et al. (2024). Robot material processing and hardware-in-the-loop-based real-time simulations. Journal of Physics: Conference Series.
- Ziada, O., Schauerte, T., Pocorni, J.K., Algabroun, H., Bolmsjö, G., et al. (2022). Robotic Window Assembly : A Simulation Study and a Proposed Self-Adaptive Software Architecture. Proceedings of the 10th Swedish Production Symposium. 111-121.
- Algabroun, H., Al-Najjar, B., Jonsson, M. (2020). A framework for the integration of digitalised maintenance systems with relevant working areas : A case study. 4th IFAC Workshop on Advanced Maintenance Engineering, Services and Technologies - AMEST 2020. 185-190.
- Algabroun, H., Al-Najjar, B., Ingwald, A. (2019). Assessment of the impact of maintenance integration within a plant using MFD : A case study. Asset Intelligence through Integration and Interoperability and Contemporary Vibration Engineering Technologies : Proceedings of the 12th World Congress on Engineering Asset Management and the 13th International Conference on Vibration Engineering and Technology of Machinery. 61-71.
- Al-Najjar, B., Algabroun, H., Jonsson, M. (2018). Smart maintenance model using cyber physical system. Paper presented at the International Conference on "Role of Industrial Engineering in Industry 4.0 Paradigm" (ICIEIND), Bhubaneswar, India, September 27-30, 2018. 1-6.
- Al-Najjar, B., Algabroun, H. (2018). A Model for Increasing Effectiveness and Profitability of Maintenance Performance : A Case Study. Engineering Asset Management 2016 : Proceedings of the 11th World Congress on Engineering Asset Management. 1-12.
- Algabroun, H., Iftikhar, M.U., Al-Najjar, B., Weyns, D. (2017). Maintenance 4.0 Framework Using Self-Adaptive Software Architecture. Proceedings of 2nd International Conference on Maintenance Engineering, IncoME-II 2017.The University of Manchester, UK.
Doctoral thesis, comprehensive summary (Other academic)
- Algabroun, H. (2020). On the development of a new digitalised maintenance approach for factories of the future. Doctoral Thesis. Växjö, Linnaeus University Press. 83.
Licentiate thesis, comprehensive summary (Other academic)
- Algabroun, H. (2017). On the development of a maintenance approach for factory of the future implementing Industry 4.0. Licentiate Thesis. Växjö, Linnaeus University Press. 40.