Aluminium parts casting scheduling based on simulated annealing

Jiménez Martín, Antonio ORCID: https://orcid.org/0000-0002-4947-8430, Mateos Caballero, Alfonso ORCID: https://orcid.org/0000-0003-4764-6047 and Hernández Diego, Josefa Zuleide ORCID: https://orcid.org/0000-0002-5374-1457 (2021). Aluminium parts casting scheduling based on simulated annealing. "Mathematics", v. 9 (n. 7); p. 741. ISSN 2227-7390. https://doi.org/10.3390/math9070741.

Descripción

Título: Aluminium parts casting scheduling based on simulated annealing
Autor/es:
Tipo de Documento: Artículo
Título de Revista/Publicación: Mathematics
Fecha: 31 Marzo 2021
ISSN: 2227-7390
Volumen: 9
Número: 7
Materias:
Palabras Clave Informales: Aluminium production process, Schedule optimization in the casting process, Simulated Annealing
Escuela: E.T.S. de Ingenieros Informáticos (UPM)
Departamento: Inteligencia Artificial
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

This paper focuses on the last stage of the aluminium production process in the context of Industry 4.0: schedule optimization in the casting process. Casting is one of the oldest manufacturing processes in which a liquid material is usually poured into a mold that contains a hollow cavity of the desired shape and then allowed to solidify. This is a complex scheduling problem in which several constraints, such as different maintenance processes, maximum stocks, machine breakdowns, work shifts, or the maximum number of mold changes per day, come into play. Four objective functions have to be taken into account simultaneously. We have to minimize both the unmet demand at the end of the schedule, and the delays in the injection process with regard to daily demands. Production costs, including the cost of electricity consumption in the injection process and gas consumption associated with melting furnaces, should be minimized. Finally, the total number of mold changes throughout the schedule must also be reduced to a minimum. The simulated annealing (SA) metaheuristic has been adapted to solve this complex optimization process and parameterized for application to a wide variety of aluminium making processes. SA efficiently solves the problem and provides an optimal solution in about three minutes.

Proyectos asociados

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Código
Acrónimo
Responsable
Título
Gobierno de España
MTM2017-86875-C3-3-R
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ID de Registro: 85771
Identificador DC: https://oa.upm.es/85771/
Identificador OAI: oai:oa.upm.es:85771
URL Portal Científico: https://portalcientifico.upm.es/es/ipublic/item/9323428
Identificador DOI: 10.3390/math9070741
URL Oficial: https://www.mdpi.com/2227-7390/9/7/741
Depositado por: iMarina Portal Científico
Depositado el: 09 Ene 2025 19:21
Ultima Modificación: 19 Feb 2025 09:52