20180918 FHWN 2016 64037 BEA Himmelverlaengert Dunkelblau ansicht
Dipl.-Ing. Dr.

Selim Erol

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Dipl.-Ing. Dr.

Selim Erol


Head of Department of Industrial Management


Campus 1 Wiener Neustadt
Johannes Gutenberg-Straße 3
2700 Wiener Neustadt
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Research Activities

  • ProcessIQ

    The aim of this project is to search, evaluate and test various technologies for the automated (AI-supported) detection of quality defects and anomalies in the process data in two product lines of a manufacturer of special machines.


    The FAMOUS (Freight Access Management for Optimizing Urban Space) project aims to evaluate legislative and technical measures for freight traffic control in cities using a comprehensive calculation and simulation model. For this purpose, the GÜMORE freight transport model is used in combination with a small-scale model for fine distribution in the urban area and the proven passenger transport model from ITS Vienna Region for access management issues in cities. In addition to traffic metrics, the reduction in greenhouse gases (CO2), energy consumption and pollutant emissions are also calculated and evaluated. In addition to the Verkehrsverbund Ost (VOR), BOKU Vienna, and hh2pro, project partners include the cities of Vienna and Wiener Neustadt.

  • DigiProTrain

    This project aims to develop and offer training courses in the field of Industry 4.0 for companies in so-called learning factories. Learning Factories represent a realistic manufacturing environment suitable for education, training, and research. They are a physical learning environment containing educational instruments and equipment, effectively creating the working conditions of a real industrial site for didactic and training purposes. The Networks Development initiative has the purpose of creating an EIT Manufacturing Marketplace that offers all the Learning Factories’ education programmes and activities. Thereby increasing the outreach and access to the Learning Factories training offer, as well as incrementing the availability of equipment suitable for testing and piloting. Funded by EIT Manufacturing as part of the Learning Factory Network Development Program.

  • IntelliProPS

    The aim of this project is (1) the research and development of new planning and control concepts based on the combination of classic methods of planning and control with methods of artificial intelligence (especially machine learning) for production scenarios with very high volatility and variability with regard to product variants, order quantities, raw material/part quality, with a simultaneous high degree of automation and a high degree of human-machine collaboration, (2) the development of a configurable simulator and demonstrator that allows production companies to use various decentralized planning and control concepts enriched with AI for production scenarios with high variability and To test, evaluate and further develop volatility in terms of product variants, order quantities, raw material/part quality (development and test bench for AI-enhanced production planning and control concepts). This project is funded by the FFG as part of the COIN construction FH for the economy program.


    The research project CO-INNO-LAB investigates regional success factors and models for co-innovation in university-run innovation labs. Studies are conducted with regional com-panies in the region, in particular small and medium-sized industrial companies (KMI), using methods of classic social research and innovative methods of intervention and action research. The role of infrastructures (university innovation labs) should also be examined. For this pur-pose, a innovation lab will be built. Another goal is to research the possibilities of digitizing the co-innovation process via combined real-virtual (cyber-physical) innovation spaces. The knowledge gained should be made available as recommendations for action, best practices and, in the case of technical developments, as conceptual prototypes.

  • CircularPro

    In the "CircularPro" project, a continuing education program for SMEs is being developed that is intended to enable product developers, product designers and development engineers to design products that are recyclable. Modules are developed with a focus on the basics and framework conditions of the circular economy, recyclable materials, circular design and construction principles and circular-based product-service systems. With these modules, participants should build up competencies in order to effectively develop sustainable and recyclable products and product-service systems in the future. In order to establish the practical relevance, case studies and practical exercises are developed for all modules, which supplement the theoretical content. The FHWN Innovation Lab provides a laboratory environment that can be used for prototyping and illustrating recyclable products. This project is funded by the FFG as part of the Innovation Camps program.


  • Princz, Gabor/Shaloo, Masoud/Erol, Selim (2023): A literature review on the prediction and monitoring of assembly and disassembly processes in discrete make-to-order production in SMEs with machine vision technologies. In: Proceedings of the 2023 10th International Conference on Industrial Engineering and Applications (Hrsg.): https://dl.acm.org/doi/10.1145/3587889.3588217. ACM. Rome, IT.
  • Shaloo, Masoud/Princz, Gabor/Erol, Selim (2023): Real-time color detection for automated production lines using CNN-based machine learning. In: Lecture Notes in Networks and Systems book series (LNNS,volume 745), International Symposium on Industrial Engineering and Automation ISIEA 2023 (Hrsg.): https://link.springer.com/chapter/10.1007/978-3-031-38274-1_15. Springer. Bozen, IT.
  • Grano, Alice/Erol, Selim (2023): Exploring the fabrication lab concept for learning sustainable co-innovation in industrial engineering education – an action research case from Austria. In: European Conference on Engineering Education, SEFI 2023 (Hrsg.). SEFI. Dublin, IR.
  • Princz, Gabor/Shaloo, Masoud/Erol, Selim (2023): Anomaly Detection in Binary Time Series Data: An unsupervised Machine Learning Approach for Condition Monitoring. In: 5th International Conference on Industry 4.0 and Smart Manufacturing ISM 2023. Lisbon. Procedia Computer Science (Hrsg.). Elsevier.
  • Shaloo, Masoud/Princz, Gabor/Erol, Selim (2023): Flexible automation of quality inspection in parts assembly using CNN-based machine learning. In: 5th International Conference on Industry 4.0 and Smart Manufacturing ISM 2023. Lisbon. Procedia Computer Science (Hrsg.). Elsevier. Lisbon, PT.
  • Grano, Alice/Erol, Selim (2023): Makerspace Goes Digital – Digital Tools to Support Collaborative Innovation in an Academic Makerspace. In: 7th International Symposium on Academic Makerspaces ISAM 2023 (Hrsg.). Pittsburgh, US.
  • Erol, Selim/Pieber, Johanna/Hofer, Florian (2022): Exploring the Fabrication Lab concept in the context of Industrial Engineering Education – An action research case from Austria. In: 3rd International Conference on Industrial Engineering and Industrial Management (Hrsg.). SCIEI. Barcelona.
  • Böhm, Jasmin/Weinfurter, Stefan/Klug, Siegrun/Erol, Selim (2022): Survey of Identifying Student and Industrial User Needs for a Newly Established Austrian University-Operated Makerspace. In: Higher Education Makerspaces Initiative (HEMI) (Hrsg.): https://ijamm.pubpub.org/pub/7rlvzm5l. Atlanta, Georgia, USA.
  • Erol, Selim/Pieber, Johanna/Hofer, Florian/Princz, Gabor (2022): Fabrication Labs as Essential Building blocks of Regional Innovations Systems. In: FHK (Hrsg.).
  • Brodschelm, Dominik/Erol, Selim/Kühnen, Jakob (2020): Integriertes Energie- und Produktionsmanagement für Industriebetriebe – eine Simulationsstudie. In: Institut für Elektrizitätswirtschaft und Energieinnovation (IEE), Technische Universität Graz (TU Graz) (Hrsg.): 10.3217/978-3-85125-734-2. Verlag der Technischen Universität Graz. Graz.
  • Erol, Selim/Klug, Siegrun (2020): Together We are Less Alone - A Concept for a Regional Open Innovation Learning Lab. In: CIRP (Hrsg.). Procedia CIRP. Graz.
  • Romauch, Martin/Erol, Selim/Kühnen, Jakob (2020): Achieving long term sustainable multicriteria goalswith operational and tactical decisions. In: https://warwick.ac.uk/fac/sci/wmg/mediacentre/wmgevents/euroma2020/proceedings/. EurOMA. online.
  • Erol, Selim (2019): Industrie 4.0 - Gedanken über die Zukunft der Produktion in Europa und aktuelle Forschungsaktivitäten in der Industrie 4.0 Pilotfabrik der TU Wien. In: Achammer, Christoph; Kovacic, Iva (Hrsg.). Klein Publishing. Wien.
  • Erol, Selim (2017): Recalling the rationale of change from process model revision comparison – A change-pattern based approach. In: Computers in Industry, Elsevier. Brussels.
  • Erol, Selim (2017): “Lotsize 1” – Effects of Individualization on Planning and Control of Production Systems. In: Wien.
  • Schumacher, Andreas/Erol, Selim/Sihn, Wilfried (2016): A maturity model for assessing Industry 4.0 readiness and maturity of manufacturing enterprises. In: CIRP (Hrsg.): https://doi.org/10.1016/j.procir.2016.07.040. Procedia CIRP. Bath / UK.
  • Erol, Selim; Wilfried, Sihn (2016): Intelligent Production Planning and Control in the Cloud – Towards a Scalable Software Architecture. In: CIRP (Hrsg.): 10.1016/j.procir.2017.01.003. Procedia CIRP. Ischia/Italy.
  • Erol, Selim (2016): Collaborative Modeling of Manufacturing Processes – a Wiki-Based Approach. In: Springer. Sydney.
  • Erol, Selim/Jäger, Andreas/Hold, Philipp/Ott, Karl/Sihn, Wilfried (2016): Tangible Industry 4.0: a scenario-based approach to learning for the future of production. In: 10.1016/j.procir.2016.03.162. CIRP. Gjøvik, Norway.
  • Erol, Selim/Hold, Philipp (2016): Keeping Track of the Physical in Assembly Processes. In: 10.1109/EDOCW.2016.7584365. IEEE. Wien.