Organisation profile

The members of the Institute for Production Technology and Systems (IPTS) carry out work on a wide range of engineering-related research questions.
When it comes to subjects, the members of the Institute concentrate on the topics of supply chain management and production management, as well as on measurement, control, plasma, production and material technology. Within these fields, we aim to answer current research questions through both experimental work and the use of digital modelling. Our overarching goal here is to provide better solution strategies for complex problems within the field of engineering.

Topics

Die Forschungsschwerpunkte des IPTS liegen im Bereich neuer Produktionstechnologien und Produktionssysteme. Dazu gehören nicht nur neue Technologien für Produktinnovationen, sondern auch die Entwicklung von Prozessen, Systemen, Komponenten, Ausrüstungen und Dienstleistungen. 

Forschungsziele sind unter anderem die Optimierung der wertschöpfenden Prozessschritte und Minderung indirekter Arbeitsschritte wie Transport, Handhabungsschritte, Nacharbeit und Qualitätsüberprüfung. 

Ein wichtiger Aspekt ist dabei immer der schonende Umgang mit den weltweit knapper werdenden Ressourcen. Innovative, effizient gestaltete Produktions- und Servicesysteme bilden einen weiteren Forschungschwerpunkt. Von besonderer Relevanz für die Forschung in der Produktion ist die ganzheitliche Bewertung von Lebenszykluskosten bei der Produktionsplanung.

  1. Journal articles › Research › Peer-reviewed
  2. Published
  3. Published

    Sensor Fusion for Power Line Sensitive Monitoring and Load State Estimation

    Schimmack, M., Belda, K. & Mercorelli, P., 14.08.2023, In: Sensors. 23, 16, 18 p., 7173.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  4. Published

    Setting controller parameters through a minimum strategy with a weighted least squares method

    Mercorelli, P., 19.07.2013, In: International Journal of Pure and Applied Mathematics. 86, 2, p. 457-463 7 p.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  5. Published

    Short-arc measurement and fitting based on the bidirectional prediction of observed data

    Fei, Z., Xu, X. & Georgiadis, A., 05.01.2016, In: Measurement Science and Technology. 27, 2, 19 p., 025013.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  6. Published

    Simple relay non-linear PD control for faster and high-precision motion systems with friction

    Zheng, C., Su, Y. & Mercorelli, P., 27.11.2018, In: IET Control Theory and Applications. 12, 17, p. 2302-2308 7 p.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  7. Published

    Simple saturated relay non-linear PD control for uncertain motion systems with friction and actuator constraint

    Zheng, C., Su, Y. & Mercorelli, P., 13.08.2019, In: IET Control Theory and Applications. 13, 12, p. 1920-1928 9 p.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  8. Published

    Single Robust Proportional-Derivative Control for Friction Compensation in Fast and Precise Motion Systems With Actuator Constraint

    Zheng, C., Su, Y. & Mercorelli, P., 01.11.2020, In: Journal of Dynamic Systems, Measurement and Control. 142, 11, 10 p., 114505.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  9. Published

    Sliding mode and model predictive control for inverse pendulum

    Schwab, K. C., Schräder, L., Mercorelli, P. & Lassen, J. T., 01.01.2019, In: WSEAS Transactions on Systems and Control. 14, p. 190-195 6 p., 23.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  10. Published

    Sliding Mode Control for a Vertical Dynamics in the Presence of Nonlinear Friction

    Ferch, T. & Mercorelli, P., 2019, In: WSEAS Transactions on Circuits and Systems. 18, p. 102-112 11 p., 17.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  11. Published

    Smarte Anpassung von Presslinienparametern: Bildgebende Sensorik und maschinelles Lernen für robustere Blechumformprozesse im Automobilbau

    Heger, J., Voß, T. & Selent, M., 04.2018, In: Industrie 4.0 Management. 34, 4, p. 53-56 4 p.

    Research output: Journal contributionsJournal articlesResearchpeer-review