cutting in the steel industry | F. Javier Martín-Campo

Cutting processes play a crucial role in the steel industry, as they directly impact material utilization, production efficiency, and product quality. These processes involve dividing steel sheets, plates, or coils into the desired shapes and sizes using techniques such as shearing, laser cutting, plasma cutting, or water jet cutting. Key characteristics of cutting processes include precision, speed, flexibility, and the ability to minimize material waste. Proper planning of cutting operations is essential to ensure optimal use of raw materials, reduce production costs, and maintain consistent quality standards. Effective cut planning also allows manufacturers to meet delivery deadlines, adapt to varying order specifications, and integrate seamlessly with downstream processes such as forming, welding, or assembly, ultimately contributing to the competitiveness and sustainability of steel production.

In (Sierra-Paradinas et al., 2021), a real-world cutting problem was studied for the Spanish company Cortichapa. The proposed model enables the design of cutting patterns for coils in stock, selecting the most suitable coil and minimizing material waste, while deviating as little as possible from customer requirements and considering the specific characteristics of each order. The problem is formulated as a 1.5-dimensional cutting problem, and the validity of the model was tested using a dataset of real company orders.

However, the cutting patterns generated by this model were sometimes incompatible with the machines, as some orders within a pattern did not meet the technical specifications of the company’s cutting equipment. This limitation highlighted the need for a more advanced model that explicitly considers machine constraints. In (Sierra-Paradinas et al., 2024), a new model was proposed in which cutting patterns are designed while minimizing the makespan and balancing the machine load, under a multi-criteria decision framework. The model’s results were again validated using real company data, as reported in (Sierra-Paradinas et al., 2023) and (Soto-Sánchez et al., 2025).

References

2025

Dataset of the doctoral thesis "Sistemas de ayuda a la decisión y optimización en problemas de corte de acero"

Óscar Soto-Sánchez, María Sierra-Paradinas, Micael Gallego, Antonio Alonso-Ayuso, F. Javier Martín-Campo, and Francisco Gortázar

Nov 2025

DOI Bib

@misc{SotoSanchezDS2025,
  doi = {10.5281/ZENODO.14601245},
  url = {https://zenodo.org/doi/10.5281/zenodo.14601245},
  author = {Soto-Sánchez, Óscar and Sierra-Paradinas, María and Gallego, Micael and Alonso-Ayuso, Antonio and Martín-Campo, F. Javier and Gortázar, Francisco},
  title = {Dataset of the doctoral thesis "Sistemas de ayuda a la decisión y optimización en problemas de corte de acero"},
  publisher = {Zenodo},
  year = {2025},
  copyright = {Creative Commons Attribution 4.0 International},
  google_scholar_id = {4TOpqqG69KYC}
}

2024

On solving the 1.5-dimensional cutting stock problem with heterogeneous slitting lines allocation in the steel industry

María Sierra-Paradinas, Óscar Soto-Sánchez, Antonio Alonso-Ayuso, F. Javier Martín-Campo, and Micael Gallego

Computers & Industrial Engineering, May 2024

DOI Bib

@article{SierraParadinas2024,
  title = {On solving the 1.5-dimensional cutting stock problem with heterogeneous slitting lines allocation in the steel industry},
  volume = {191},
  issn = {0360-8352},
  url = {http://dx.doi.org/10.1016/j.cie.2024.110120},
  doi = {10.1016/j.cie.2024.110120},
  journal = {Computers &amp; Industrial Engineering},
  publisher = {Elsevier BV},
  author = {Sierra-Paradinas, María and Soto-Sánchez, Óscar and Alonso-Ayuso, Antonio and Martín-Campo, F. Javier and Gallego, Micael},
  year = {2024},
  month = may,
  pages = {110120},
  google_scholar_id = {kNdYIx-mwKoC},
  dimensions = {true}
}

2023

Subset of instances used in article "On solving the 1.5-dimensional cutting stock problem with heterogeneous slitting lines allocation in the steel industry"

María Sierra-Paradinas, Óscar Soto-Sánchez, Antonio Alonso-Ayuso, F. Javier Martín-Campo, and Micael Gallego

May 2023

DOI Bib

@misc{SierraParadinasDS2023,
  doi = {10.5281/ZENODO.10123915},
  url = {https://zenodo.org/doi/10.5281/zenodo.10123915},
  author = {Sierra-Paradinas, María and Soto-Sánchez, Óscar and Alonso-Ayuso, Antonio and Martín-Campo, F. Javier and Gallego, Micael},
  title = {Subset of instances used in article "On solving the 1.5-dimensional cutting stock problem with heterogeneous slitting lines allocation in the steel industry"},
  publisher = {Zenodo},
  year = {2023},
  copyright = {Creative Commons Attribution 4.0 International},
  google_scholar_id = {_kc_bZDykSQC}
}

2021

An exact model for a slitting problem in the steel industry

María Sierra-Paradinas, Óscar Soto-Sánchez, Antonio Alonso-Ayuso, F. Javier Martín-Campo, and Micael Gallego

European Journal of Operational Research, Nov 2021

DOI Bib

@article{SierraParadinas2021,
  title = {An exact model for a slitting problem in the steel industry},
  volume = {295},
  issn = {0377-2217},
  url = {http://dx.doi.org/10.1016/j.ejor.2021.02.048},
  doi = {10.1016/j.ejor.2021.02.048},
  number = {1},
  journal = {European Journal of Operational Research},
  publisher = {Elsevier BV},
  author = {Sierra-Paradinas, María and Soto-Sánchez, Óscar and Alonso-Ayuso, Antonio and Martín-Campo, F. Javier and Gallego, Micael},
  year = {2021},
  month = nov,
  pages = {336–347},
  google_scholar_id = {MXK_kJrjxJIC},
  dimensions = {true}
}