Objective
Sensor technology has become increasingly important (e.g., Industry 4.0, IoT). Large numbers of machines and products are equipped with sensors to constantly monitor their condition. Usually, the condition of an entire system is inferred through sensors only focusing on certain parts of the entire system by means of a multiplicity of methods and techniques. However, for small components as well as relatively inexpensive or immutable parts of a machine, asset or product, sometimes it is either technically not possible or uneconomical to embed sensors.
This project aims to explore a system-oriented concept of how to monitor individual components of a complex technical system without including additional sensor technology. By using already existing sensors from the environment combined with machine learning techniques, it seems to be possible to infer the condition of a system component, without actually observing it. In consequence, condition monitoring or additional services based on the component’s behavior can be developed without overcoming the challenges of sensor implementation.
Funding
Trelleborg
Duration
01.01.2018 – 30.06.2021
Partners
Involved DSI Researchers
Publications
Martin, D.; Kühl, N.; Satzger, G.
2021. Business & information systems engineering, 63 (3), 315–323. doi:10.1007/s12599-021-00689-w
Martin, D.; Kühl, N.; Schwenk, M.
2021. Proceedings : 2021 IEEE 23rd Conference on Business Informatics, CBI 2021, Virtual Conference 1-3 September 2021, Volume 2 – CBI Forum and Workshop Papers. Ed.: J.P.A. Almeida, 1–9, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CBI52690.2021.10049
Martin, D.; Kühl, N.; Maleshkova, M.
2020. Smart Service Management: Design Guidelines and Best Practices. Hrsg.: Maria Maleshkova, Niklas Kühl, Philipp Jussen, 7–21, Springer International Publishing. doi:10.1007/978-3-030-58182-4_2
Martin, D.; Kühl, N.; Bischhoffshausen, J. K. von
2020. Smart Service Management: Design Guidelines and Best Practices. Hrsg.: Maria Maleshkova, Niklas Kühl, Philipp Jussen, 179–191, Springer International Publishing. doi:10.1007/978-3-030-58182-4_16
Martin, D.; Kühl, N.; Bischhoffshausen, J. K. von; Satzger, G.
2020. Designing for Digital Transformation. Co-Creating Services with Citizens and Industry - 15th International Conference on Design Science Research in Information Systems and Technology, DESRIST 2020, December 2–4, 2020. Ed.: S. Hofmann, 457–468, Springer. doi:10.1007/978-3-030-64823-7_44
Martin, D.; Kunze von Bischhoffshausen, J.; Hensel, A.; Strandberg, J.
2020. Proceedings of the 12th International Fluid Power Conference (IFK), Dresden, Oktober 2020
Martin, D.; Spitzer, P.; Kühl, N.
2020. 53rd Annual Hawaii International Conference on System Sciences (HICSS-53), Grand Wailea, Maui, HI, January 7-10, 2020
Martin, D.; Hirt, R.; Kühl, N.
2019. 14. Internationale Tagung Wirtschaftsinformatik 2019 (WI 2019), Siegen, Germany, February 24-27
Martin, D.; Kühl, N.
2019. Proceedings of the 52nd Annual Hawaii International Conference on System Sciences : January 8-11, 2019, Maui, Hawaii. Ed.: Tung X. Bui, 1005–1012, University of Hawaii at Manoa, Hamilton Library, ScholarSpace. doi:10.24251/HICSS.2019.124
Martin, D.; Schüle, C.; Kunze von Bischhoffshausen, J.
2018. 20th ISC: International Sealing Conference, Stuttgart, October 10-11, 2018