@misc{11792,
  abstract     = {{To facilitate the drying process and enhance the properties of oil palm wood, oil palm boards were mechanically pre-dewatered and thermo-hygro-mechanically (THM) densified. The thickness of the boards was reduced with compression ratios of 40%, 60% and 75%. Since densified wood tends to recover from compression, especially under humid conditions, this study examined the set-recovery and the hygroscopic behavior of THM densified oil palm wood. The equilibrium moisture content (EMC), differential swelling and swelling coefficient, linear swelling and shrinkage as well as the differential swelling anisotropy were determined under climate conditions with different relative humidity (RH) (20°C/35% RH, 20°C/65% RH and 20°C/85% RH). The maximum swelling was measured after water soaking and the remaining set-recovery was evaluated after re-drying at 103°C. The EMC was reduced by the THM process by around 20%. In the direction of compression (thickness), the densified specimens show higher values for all analyzed swelling and shrinkage parameters than the undensified specimens from the equivalent position within the trunk. The maximum swelling in thickness of 22–38% during water soaking is mostly reversed by shrinkage during re-drying and a comparably low remaining set-recovery of 3–8% is measured at oven dry condition.}},
  author       = {{Kölli, Nathan and Frühwald-König, Katja and Hackel, Martin}},
  booktitle    = {{Wood Material Science & Engineering}},
  issn         = {{1748-0280}},
  keywords     = {{Densification, set-recovery, swelling and shrinkage}},
  pages        = {{1--12}},
  publisher    = {{Taylor & Francis}},
  title        = {{{Hygroscopic behavior of thermo-hygro-mechanical (THM) densified oil palm sawn timber}}},
  doi          = {{10.1080/17480272.2024.2381100}},
  year         = {{2024}},
}

@inbook{6919,
  abstract     = {{Programmable logic controllers (PLCs) have become the industry standard and have replaced hard-wired electrical devices used to control production equipment. With its advanced use, the PLC is increasingly becoming an important part of engineering. Therefore, it is essential to effectively teach students how PLCs work and how to program them through practical exercises. The goal of this paper is to present a training set used to program a PLC that fulfills the needs of industrial engineering students. The training set presented here allows students to learn about different industrial applications of PLCs, and to program such PLCs themselves.}},
  author       = {{Nikolenko, Alexander and Meyer, Frederic and Hinrichsen, Sven}},
  booktitle    = {{Advances in Intelligent Systems and Computing}},
  editor       = {{Nunes, I.}},
  isbn         = {{9783030513689}},
  issn         = {{2194-5357}},
  keywords     = {{PLC, Digitization, Industrial Engineering, Training Set}},
  pages        = {{69--74}},
  publisher    = {{Springer}},
  title        = {{{How to Teach Digital Tools for Process Automation in Industrial Engineering Education}}},
  doi          = {{10.1007/978-3-030-51369-6_10}},
  volume       = {{1207}},
  year         = {{2020}},
}

@inproceedings{2141,
  abstract     = {{Sensor and information fusion is recently a major topic which becomes important in machine diagnosis and conditioning for complex production machines and process engineering. It is a known fact that distributed automation systems have a major impact on signal processing and pattern recognition for machine diagnosis. Therefore, it is necessary to research and develop smart diagnosis methods which are applicable for distributed systems like resource-limited cyber-physical systems. In this paper we propose an new approach for sensor and information fusion based on Evidence Theory and socio-psychological decision-making. We show that context based condition monitoring is instantiated even in conflict situations, oc-curing in real life scenarios permanently. A simple but effective importance measure is proposed which controls the significance of conditioning propositions in a system.}},
  author       = {{Mönks, Uwe and Lohweg, Volker}},
  booktitle    = {{18th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)}},
  isbn         = {{978-1-4799-0862-2}},
  issn         = {{1946-0759 }},
  keywords     = {{Decision making, Robot sensing systems, Reliability, Production, Context, Fuzzy set theory, Data integration}},
  title        = {{{Machine Conditioning by Importance Controlled Information Fusion}}},
  doi          = {{10.1109/ETFA.2013.6647984}},
  year         = {{2013}},
}

@inproceedings{2107,
  abstract     = {{In this paper we propose a novel, extended perspective on evidential aggregation rules in machine condition monitoring. First, aspects regarding the interconnections between Dempster-Shafer, Fuzzy Set, and Possibility Theory are shown. Subsequently, a novel approach for direct determination of basic probability assignments using Fuzzy membership functions is proposed. Finally, it is applied to a pipe extrusion line's condition monitoring system, considering and reducing pairwise conflicts.}},
  author       = {{Mönks, Uwe and Voth, Karl and Lohweg, Volker}},
  booktitle    = {{IEEE CIP 2012, Third International Workshop on Cognitive Information Processing, May 28-30 2012, Parador de Baiona, Spain}},
  isbn         = {{978-1-4673-1877-8}},
  issn         = {{2327-1698 }},
  keywords     = {{Sensor phenomena and characterization, Production, Sensor fusion, Fuzzy set theory, Conferences, Possibility theory}},
  title        = {{{An Extended Perspective on Evidential Aggregation Rules in Machine Conditioning}}},
  doi          = {{10.1109/CIP.2012.6232905}},
  year         = {{2012}},
}