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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.
| Título: | Aluminium parts casting scheduling based on simulated annealing |
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| Autor/es: |
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| 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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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.
| ID de Registro: | 85771 |
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| 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 |
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