Options
Rodríguez Aguilar, Román
Improving a Manufacturing Process using Recursive Artificial Intelligence
Design of a logistics network using analytical techniques and agent-based simulation
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.
2021
,
Marmolejo Saucedo, José Antonio
,
Rodríguez Aguilar, Román
,
Meza Callejas, Gerardo
,
Kelley Urbieta, Mitchell Santiago
,
Peregrina Acasuso, Saul Fernando
,
Gutierrez Girault, Juan Pablo
Business Logistics, or Supply Chain, has acquired a notorious relevance in current business management, due to its highly significant impact on the success of the production and service sectors. This work proposes the design of a supply chain that considers disruptive scenarios and improves the level of service compared to the current situation. Discrete event simulation techniques are used in conjunction with agent-based modeling to define production orders. A hypothetical case study was developed to show the performance of the proposal. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.