Improving a Manufacturing Process using Recursive Artificial Intelligence
Journal
Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems
IFIP Advances in Information and Communication Technology
ISSN
1868-4238
1868-422X
Date Issued
2021
Author(s)
Marmolejo Saucedo, José Antonio
Romero Perea, Uriel Abel
Garrido Vaqueiro, Manuel
Robredo Hernández, Regina
Sánchez Ramírez , Fernando
Martínez , Ana Paula
Type
Resource Types::text::conference output::conference proceedings::conference paper
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. ©2021, IFIP International Federation for Information Processing.