In the last years, the increase of data availability together with enhanced resource flexibility shed light on the possibility to develop planning and control methods with real-time inputs. Literature is rich of approaches to simulate, to quickly evaluate system performances, and to take decisions based on optimization criteria. Further, simulation has been identified as one of the pillars for the Industry 4.0 revolution. However, the lack of a generally recognized approach and methodology to deal with real-time decision-making through simulation is evident. Simulation approaches can and should play a central role in industry for the years to come. This position paper analyses the current research context with a brief state of the art on existing approaches, includes considerations about the issues for implementing Real-Time Simulation (RTS) concepts and their current state of development. Finally, it outlines research directions for the simulation community.

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Simulation classes have the main advantage of deeply involving and stimulating students through intensive work in computer laboratories and projects. The counterpart is often the lack of the real system that is subject to simulation modeling. Creating, building and validating a simulation model of a system that cannot be observed represent a real obstacle for student learning. In this paper, we describe the experience from an educational project launched in a course of manufacturing systems for mechanical engineering students in which discrete event simulation plays a fundamental role in performance evaluation. The project has been designed to exploit student interaction with a LEGO R -based physical system. Students have the possibility to learn from the physical system and making experiments together with the simulation model built during project activities. The project details are also described with the hope that the project becomes a simulation case study and be replicated in other courses.

Recently, the connection between manufacturing systems and their digital counterparts has become of great significance for planning and control activities in a shortterm scope. However, the alignment of a digital model with a very dynamic system is not always guaranteed, and traditional validation techniques cannot be used since they are designed for off-line simulators and rely on the availability of a large amount of data. This work develops a novel validation procedure inspired by signal-processing theory and a novel approach called quasi Trace Driven Simulation. The procedure is coherent with a Real-Time Simulation framework since it does not require large datasets to provide a good solution. The approach has been tried on test cases which demonstrated its applicability to a manufacturing environment.

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