Improving the flexibility of production scheduling in flat steel production through standard and AI-based approaches: challenges and perspectives - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Energies Année : 2021

Improving the flexibility of production scheduling in flat steel production through standard and AI-based approaches: challenges and perspectives

Résumé

In recent years, the European Steel Industry, in particular flat steel production, is facing an increasingly competitive market situation. The product price is determined by competition, and the only way to increase profit is to reduce production and commercial costs. One method to increase production yield is to create proper scheduling for the components on the available machines, so that an order is timely completed, optimizing resource exploitation and minimizing delays. The optimization of production using efficient scheduling strategies has received ever increasing attention over time and is one of the most investigated optimization problems. The paper presents three approaches for improving flexibility of production scheduling in flat steel facilities. Each method has different scopes and modelling aspects: an auction-based multi-agent system is used to deal with production uncertainties, a multi-objective mixed-integer linear programming-based approach is applied for global optimal scheduling of resources under steady conditions, and a continuous flow model approach provides long-term production scheduling. Simulation results show the goodness of each method and their suitability to different production conditions, by highlighting their advantages and limitations.
Fichier principal
Vignette du fichier
509922_1_En_49_Chapter.pdf (815.77 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03287705 , version 1 (15-07-2021)

Licence

Paternité

Identifiants

Citer

Vincenzo Iannino, Valentina Colla, Alessandro Maddaloni, Jens Brandenburger, Ahmad Rajabi, et al.. Improving the flexibility of production scheduling in flat steel production through standard and AI-based approaches: challenges and perspectives. AIAI 2021: 17th IFIP International Conference on Artificial Intelligence Applications and Innovations, Jun 2021, Hersonissos, Crete, Greece. pp.619-632, ⟨10.1007/978-3-030-79150-6_49⟩. ⟨hal-03287705⟩
144 Consultations
33 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More