TY - GEN
T1 - Improving the Flexibility of Production Scheduling in Flat Steel Production Through Standard and AI-Based Approaches
T2 - 17th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2021
AU - Iannino, Vincenzo
AU - Colla, Valentina
AU - Maddaloni, Alessandro
AU - Brandenburger, Jens
AU - Rajabi, Ahmad
AU - Wolff, Andreas
AU - Ordieres, Joaquin
AU - Gutierrez, Miguel
AU - Sirovnik, Erwin
AU - Mueller, Dirk
AU - Schirm, Christoph
N1 - Publisher Copyright:
© 2021, The Author(s).
PY - 2021/1/1
Y1 - 2021/1/1
N2 - 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.
AB - 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.
KW - Agent-based
KW - Continuous flow model
KW - Dynamic production scheduling
KW - Flat steel industry
KW - Hybrid approach
KW - Mixed-integer linear programming
U2 - 10.1007/978-3-030-79150-6_49
DO - 10.1007/978-3-030-79150-6_49
M3 - Conference contribution
AN - SCOPUS:85111808908
SN - 9783030791490
T3 - IFIP Advances in Information and Communication Technology
SP - 619
EP - 632
BT - Artificial Intelligence Applications and Innovations - 17th IFIP WG 12.5 International Conference, AIAI 2021, Proceedings
A2 - Maglogiannis, Ilias
A2 - Macintyre, John
A2 - Iliadis, Lazaros
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 25 June 2021 through 27 June 2021
ER -