An exact model for a slitting problem in the steel industry

被引:10
作者
Sierra-Paradinas, Maria [1 ,2 ]
Soto-Sanchez, Oscar [2 ]
Alonso-Ayuso, Antonio [2 ]
Martin-Campo, F. Javier [3 ]
Gallego, Micael [2 ]
机构
[1] IDOM Consulting, Engn, Architecture, Bilbao, Spain
[2] Univ Rey Juan Carlos, Dept Comp Sci Comp Architecture Comp Languages &, Mostoles, Spain
[3] Univ Complutense Madrid, Inst Matemat Interdisciplinar, Dept Estadist & Invest Operat, Madrid, Spain
关键词
Cutting; Steel industry; Mixed integer linear optimisation; CUTTING STOCK PROBLEM; LINEAR-PROGRAMMING APPROACH; USABLE LEFTOVERS; TRIM-LOSS; OPTIMIZATION; PACKING;
D O I
10.1016/j.ejor.2021.02.048
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
From an economic point of view, the steel industry plays an important role and, when it comes to responding to new challenges, innovation is a crucial factor. This paper proposes a mathematical methodology to solve the slitting problem in a steel company located in Europe. The slitting problem occurs when large width steel coils are slit into narrower coils, known as strips, to meet the requirements of the customers. A major challenge here is defining a slitting plan to fulfil all these requirements, as well as ongoing operational constraints and customer demands. The company looks for a reduction of the leftovers generated in the entire process, while maximising the overall accuracy of the orders. These leftovers may be used in the future as part of new orders provided they are able to respond to specific requirements, or otherwise they are discarded and considered as scrap. This paper introduces a novel mixed integer linear optimisation model to respond to a specific slitting problem. The model is validated with real data and it outperforms the results obtained by the company in different ways: by adjusting the orders that are to be served, by reducing the amount of scrap and by using the retails for future orders. Furthermore, the model is solved in only a few minutes, while the company needs several hours to prepare the scheduling in the current operating process. (c) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页码:336 / 347
页数:12
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