A discrete process modelling and simulation methodology for industrial systems within the concept of digital twinsA discrete process modelling and simulation methodology for industrial systems within the concept of digital twins Peer-Reviewed Journal Publication Δημοσίευση σε Περιοδικό με Κριτές 2023-08-222022enA generic well-defined methodology for the construction and operation of dynamic process models of discrete industrial systems following a number of well-defined steps is introduced. The sequence of steps for the application of the method as well as the necessary inputs, conditions, constraints and the results obtained are defined. The proposed methodology covers the classical offline modelling and simulation applications as well as their online counterpart, which use the physical system in the context of digital twins, with extensive data exchange and interaction with sensors, actuators and tools from other scientific fields as analytics and optimisation. The implemented process models can be used for what-if analysis, comparative evaluation of alternative scenarios and for the calculation of key performance indicators describing the behaviour of the physical systems under given conditions as well as for online monitoring, management and adjustment of the physical industrial system operations with respect to given rules and targets. An application of the proposed methodology in a discrete industrial system is presented, and interesting conclusions arise and are discussed. Finally, the open issues, limitations and future extensions of the research are considered.This work was supported by European Union’s Horizon 2020 program project FACTLOG under grant agreement number H2020-869951.http://creativecommons.org/licenses/by/4.0/Applied Sciences122Tsinarakis_et_al_Appl. Sci._12(2)_2022.pdfChania [Greece]Library of TUC2023-08-22application/pdf998.5 kBfree Tsinarakis Georgios Τσιναρακης Γεωργιος Sarantinoudis Nikolaos Σαραντινουδης Νικολαος Arampatzis Georgios Αραμπατζης Γεωργιος MDPI Process modelling Digital twins Cognitive manufacturing Industrial systems Industry 4.0 Discrete event systems Petri nets Internet of Things Optimisation Analytics