Scientific Publications

SCIENTIFIC PUBLICATIONS


von Stietencron, M., Lewandowski, M., Lepenioti, K., Bousdekis, A., Hribernik, K., Apostolou, D., Mentzas, G. (2020) Streaming Analytics in Edge-Cloud Environment for Logistics Processes. In: Lalic B., Majstorovic V., Marjanovic U., von Cieminski G., Romero D. (eds) Advances in Production Management Systems. Towards Smart and Digital Manufacturing. APMS 2020. IFIP Advances in Information and Communication Technology, vol 592. Springer, Cham.
Lepenioti, K., Pertselakis, M., Bousdekis, A., Louca, A., Lampathaki, F., Apostolou, D., Mentzas, G., Anastasiou, S. (2020). Machine Learning for Predictive and Prescriptive Analytics of Operational Data in Smart Manufacturing In: Dupuy-Chessa S., Proper H. (eds) Advanced Information Systems Engineering Workshops. CAiSE 2020. Lecture Notes in Business Information Processing, vol 382. Springer, Cham
Bousdekis, A., Apostolou, D. and Mentzas, G. (2020). Predictive Maintenance in the 4th Industrial Revolution: Benefits, Business Opportunities, and Managerial Implications In: IEEE Engineering Management Review, vol. 48, no. 1, pp. 57-62, 1 Firstquarter,march 2020, doi: 10.1109/EMR.2019.2958037.
Karagiorgou, S., Vafeiadis, G., Ntalaperas, D. ,Lykousas, N., Vergeti, D. and Alexandrou, D. (2019). Unveiling Trends and Predictions in Digital Factories In: 15th International Conference on Distributed Computing in Sensor Systems (DCOSS), Santorini Island, Greece, 2019, pp. 326-332, doi: 10.1109/DCOSS.2019.00073.
Bousdekis A., Lepenioti K., Apostolou D., Mentzas G. (2019). Decision Making in Predictive Maintenance: Literature Review and Research Agenda for Industry 4.0 In: Science Direct IFAC PapersOnLine 52-13 (2019) 607–612
Bousdekis A., Lepenioti K., Ntalaperas D., Vergeti D., Apostolou D., Boursinos V. (2019). A RAMI 4.0 View of Predictive Maintenance: Software Architecture, Platform and Case Study in Steel Industry. In: Proper H., Stirna J. (eds) Advanced Information Systems Engineering Workshops. CAiSE 2019. Lecture Notes in Business Information Processing, vol 349. Springer, Cham
Pertselakis M., Lampathaki F., Petrali P. (2019).Predictive Maintenance in a Digital Factory Shop-Floor: Data Mining on Historical and Operational Data Coming from Manufacturers’ Information Systems. In: Proper H., Stirna J. (eds) Advanced Information Systems Engineering Workshops. CAiSE 2019. Lecture Notes in Business Information Processing, vol 349. Springer, Cham
Lepenioti K., Bousdekis A., Apostolou D., Mentzas G. (2019). Prescriptive analytics: Literature review and research challenges, International Journal of Information Management, vol 50, 57-70, Elsevier
Bousdekis A., Mentzas G., Hribernik K., Lewandowski M., von Stietencron M., Thoben KD. (2019). A Unified Architecture for Proactive Maintenance in Manufacturing Enterprises in: Popplewell K., Thoben KD., Knothe T., Poler R. (eds) Enterprise Interoperability VIII. Proceedings of the I-ESA Conferences, vol 9. Springer, Cham
Lepenioti K., Bousdekis A., Apostolou D., Mentzas G. (2019). Prescriptive Analytics: A Survey of Approaches and Methods in: Abramowicz W., Paschke A. (eds) Business Information Systems Workshops. BIS 2018. Lecture Notes in Business Information Processing, vol 339. Springer, Cham
Hribernik, K., Von Stietencron, M., Bousdekis, A., Bredehorst, B., Mentzas, G., Thoben, K.D. (2018). Towards a Unified Predictive Maintenance System - A Use Case in Production Logistics in Aeronautics, Procedia Manufacturing, vol 16, 131-138, Elsevier
Thoben, K. D., Ait‐Alla, A., Franke, M., Hribernik, K., Lütjen, M., & Freitag, M. (2018). Real‐time Predictive Maintenance Based on Complex Event Processing In: Enterprise Interoperability: Smart Services and Business Impact of Enterprise Interoperability, 291-296
Mentzas, G., Hribernik, K., Thoben, K.D., Kiritsis, D., Mousavi, A., (2018). Part 6 Summary: Predictive Maintenance in Industry 4.0 – Methodologies, Tools and Interoperable Applications in Zelm, M., Jaekel, F.W., Doumeingts, G. and Wollschlaeger, M. (ed.) Enterprise Interoperability: Smart Services and Business Impact of Enterprise Interoperability, First Edition. ISTE Ltd and John Wiley & Sons, Inc., pp. 233 – 237
Bredehorst, B., Peters, O., Versteeg, J., Neuhaus, M., Hans, C., Von Stietencron, M (2018). Using Sensor Data for Predictive Maintenance of a Complex Transportation Asset in Zelm, M., Jaekel, F.W., Doumeingts, G. and Wollschlaeger, M. (ed.) Enterprise Interoperability: Smart Services and Business Impact of Enterprise Interoperability, First Edition. ISTE Ltd and John Wiley & Sons, Inc., pp. 239 – 245
Zanardi, D., Barbieri, M., Uguccioni, G. (2018). DRIFT: A Data‐driven Failure Mode, Effects and Criticality Analysis Tool in Zelm, M., Jaekel, F.W., Doumeingts, G. and Wollschlaeger, M. (ed.) Enterprise Interoperability: Smart Services and Business Impact of Enterprise Interoperability, First Edition. ISTE Ltd and John Wiley & Sons, Inc., pp. 285 – 290
Keraron, Y. (2018). The Standards as Critical Means of Integration of Advanced Maintenance Approaches to Production Systems in Zelm, M., Jaekel, F.W., Doumeingts, G. and Wollschlaeger, M. (ed.) Enterprise Interoperability: Smart Services and Business Impact of Enterprise Interoperability, First Edition. ISTE Ltd and John Wiley & Sons, Inc., pp. 297 – 304
Bousdekis A., Mentzas G. (2018). A Proactive Model for Joint Maintenance and Logistics Optimization in the Frame of Industrial Internet of Things in: Sifaleras A., Petridis K. (eds) Operational Research in the Digital Era – ICT Challenges. Springer Proceedings in Business and Economics (pp. 23-45). Springer, Cham
Bousdekis, A., Papageorgiou, N., Magoutas, B., Apostolou, D., & Mentzas, G. (2018).Enabling condition-based maintenance decisions with proactive event-driven computing, Computers in Industry, 100, 173-183
Bousdekis, A., Papageorgiou, N., Magoutas, B., Apostolou, D., & Mentzas, G. (2017).Information Processing for Generating Recommendations Ahead of Time in an IoT-Based Environment, International Journal of Monitoring and Surveillance Technologies Research (IJMSTR), 5(4), 38-62
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