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Rodríguez Aguilar, Román
Improving a Manufacturing Process using Recursive Artificial Intelligence
A proposal for the supply chain design : a digitization approach
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.
2018
,
Marmolejo Saucedo, José Antonio
,
Retana-Blanco, Brenda
,
Pedraza-Arroyo, Erika
,
Rodríguez Aguilar, Román
The logistics network of an automotive company in Mexico, was analyzed to propose a better logistics network in the country to improve delivery times to customers. The network design considers elements of digitization of Greenfield Analysis and Network Optimization processes. Taking into account the information given by the company, it was possible to obtain optimal scenarios for better operation, which involved the construction of distribution centers throughout Mexico. © 2020 Jose Antonio Marmolejo-Saucedo et al., licensed to EAI.