D'Amico, Davide R.Sarkar, A.Karray, H.Addepalli, SriErkoyuncu, John Ahmet2023-01-262023-01-262022-10-26D'Amico RD, Sarkar A, Karray H, et al., (2022) Detecting failure of a material handling system through a cognitive twin. In: 10th IFAC Conference on Manufacturing Modelling, Management and Control MIM 2022, 22-24 June 2022, Nantes, France2405-8963https://doi.org/10.1016/j.ifacol.2022.10.128https://dspace.lib.cranfield.ac.uk/handle/1826/19041This paper describes a methodology for developing a digital twin (DT) based on a rich semantic model and principles of system engineering. The aim is to provide a general model of digital twins (DT) that can improve decision making based on semantic reasoning on real-time system monitoring. The methodology has been tested on a laboratory pilot plant that acts as a material handling system. The key contribution of this research is to propose a generic information model for DT using foundational ontology and principles of systems engineering. The efficacy of the proposed methodology is demonstrated by the automatic detection of a component level failure using semantic reasoning.enAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Digital twincognitive twinontologyBFOIOFCCOknowledge graphSPARQLmaterial handling systemsFesto MPSConference paper