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Conference Papers Year : 2021

Improving a Manufacturing Process using Recursive Artificial Intelligence

Abstract

This work explores the improvements that can be made in the process of parametrization of discrete-event simulation models. A manufacturing process is modeled through queuing systems and alternative decisions to perform production, transport, and merchandise handling tasks. The use of recursive artificial intelligence is suggested to improve the quality of the parameters used in the simulation model. Specifically, a vector support machine is used for statistical learning. A relevant characteristic of the proposed model is the integration of different information technology platforms so that the simulation can be recursive.
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hal-03806538 , version 1 (07-10-2022)

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Jose Antonio Marmolejo-Saucedo, Roman Rodriguez-Aguilar, Uriel Perea, Manuel Garrido Vaqueiro, Regina Robredo Hernandez, et al.. Improving a Manufacturing Process using Recursive Artificial Intelligence. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2021, Nantes, France. pp.266-275, ⟨10.1007/978-3-030-85910-7_28⟩. ⟨hal-03806538⟩
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