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Rodríguez Aguilar, Román
Improving a Manufacturing Process using Recursive Artificial Intelligence
2021
,
Marmolejo Saucedo, José Antonio
,
Rodríguez Aguilar, Román
,
Romero Perea, Uriel Abel
,
Garrido Vaqueiro, Manuel
,
Robredo Hernández, Regina
,
Sánchez Ramírez , Fernando
,
Martínez , Ana Paula
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. ©2021, IFIP International Federation for Information Processing.