Abstract
Manufacturing conditions are unpredictable due to the influence of unforeseen factors, such as material supply failures, unplanned machine breakdowns, process disruptions. Discrete Event Simulation (DES) is a method of simulating the behaviour and performance of a manufacturing process, facility, or system. It is a robust tool that can strongly support manufacturers in various aspects and stages of production processes thanks to its great agility. There are numerous studies on applications of DES that can be found in the literature. Almost all studies and approaches are off-line analyses and typically involve manual tasks to process simulation results and apply them in real manufacturing execution. Recently, the advancement in cloud computing, big data, Internet of Things (IoT), and Artificial Intelligence (AI) brings huge impact to manufacturing and drives the development of smart manufacturing. The integration of simulated data provided from DES and real data captured in IoT platforms makes it possible to provide a profound analysis of a smart manufacturing system. This chapter aims to discuss the utilization of DES in smart manufacturing, with actual use cases as examples.
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This research is supported by the Agency for Science, Technology and Research (A*STAR) under its Advanced Manufacturing & Engineering (AME) Industry Alignment Funding - Pre-positioning funding scheme (Project No: A1723a0035).
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Li, W., Huynh, B.H., Akhtar, H., Myo, K.S. (2021). Discrete Event Simulation as a Robust Supporting Tool for Smart Manufacturing. In: Toro, C., Wang, W., Akhtar, H. (eds) Implementing Industry 4.0. Intelligent Systems Reference Library, vol 202. Springer, Cham. https://doi.org/10.1007/978-3-030-67270-6_11
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