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2019 | OriginalPaper | Buchkapitel

High Speed Simulation Analytics

verfasst von : Simon J. E. Taylor, Anastasia Anagnostou, Tamas Kiss

Erschienen in: Simulation for Industry 4.0

Verlag: Springer International Publishing

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Abstract

Simulation, especially Discrete-event simulation (DES) and Agent-based simulation (ABS), is widely used in industry to support decision making. It is used to create predictive models or Digital Twins of systems used to analyse what-if scenarios, perform sensitivity analytics on data and decisions and even to optimise the impact of decisions. Simulation-based Analytics, or just Simulation Analytics, therefore has a major role to play in Industry 4.0. However, a major issue in Simulation Analytics is speed. Extensive, continuous experimentation demanded by Industry 4.0 can take a significant time, especially if many replications are required. This is compounded by detailed models as these can take a long time to simulate. Distributed Simulation (DS) techniques use multiple computers to either speed up the simulation of a single model by splitting it across the computers and/or to speed up experimentation by running experiments across multiple computers in parallel. This chapter discusses how DS and Simulation Analytics, as well as concepts from contemporary e-Science, can be combined to contribute to the speed problem by creating a new approach called High Speed Simulation Analytics. We present a vision of High Speed Simulation Analytics to show how this might be integrated with the future of Industry 4.0.

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Titel: High Speed Simulation Analytics
verfasst von: Simon J. E. Taylor
Anastasia Anagnostou
Tamas Kiss
Verlag: Springer International Publishing
Buch: Simulation for Industry 4.0
Print ISBN: 978-3-030-04136-6

Electronic ISBN: 978-3-030-04137-3

Copyright-Jahr: 2019
DOI: https://doi.org/10.1007/978-3-030-04137-3_11

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