| Title: | Reduction of surface defects by optimization of casting speed using genetic programming : an industrial case study |
|---|
| Authors: | ID Kovačič, Miha (Author)
ID Župerl, Uroš (Author)
ID Gusel, Leo (Author)
ID Brezočnik, Miran (Author) |
|---|
| Files: |  APEM18-4_501-511.pdf (1,19 MB)
MD5: 8625823A90B4D8547F97A9EF4945E35E
 https://apem-journal.org/Archives/2023/APEM18-4_501-511.pdf
|
|---|
| Language: | English |
|---|
| Work type: | Article |
|---|
| Typology: | 1.01 - Original Scientific Article |
|---|
| Organization: | FS - Faculty of Mechanical Engineering
|
|---|
| Abstract: | Štore Steel Ltd. produces more than 200 different types of steel with a continuous caster installed in 2016. Several defects, mostly related to thermomechanical behaviour in the mould, originate from the continuous casting process. The same casting speed of 1.6 m/min was used for all steel grades. In May 2023, a project was launched to adjust the casting speed according to the casting temperature. This adjustment included the steel grades with the highest number of surface defects and different carbon content: 16MnCrS5, C22, 30MnVS5, and 46MnVS5. For every 10 °C deviation from the prescribed casting temperature, the speed was changed by 0.02 m/min. During the 2-month period, the ratio of rolled bars with detected surface defects (inspected by an automatic control line) decreased for the mentioned steel grades. The decreases were from 11.27 % to 7.93 %, from 12.73 % to 4.11 %, from 16.28 % to 13.40 %, and from 25.52 % to 16.99 % for 16MnCrS5, C22, 30MnVS5, and 46MnVS5, respectively. Based on the collected chemical composition and casting parameters from these two months, models were obtained using linear regression and genetic programming. These models predict the ratio of rolled bars with detected surface defects and the length of detected surface defects. According to the modelling results, the ratio of rolled bars with detected surface defects and the length of detected surface defects could be minimally reduced by 14 % and 189 %, respectively, using casting speed adjustments. A similar result was achieved from July to November 2023 by adjusting the casting speed for the other 27 types of steel. The same was predicted with the already obtained models. Genetic programming outperformed linear regression. |
|---|
| Keywords: | continuous casting of steel, surface defects, automatic control, machine learning, modelling, optimisation, prediction, linear regression, genetic programming |
|---|
| Publication status: | Published |
|---|
| Publication version: | Version of Record |
|---|
| Submitted for review: | 03.11.2023 |
|---|
| Article acceptance date: | 21.12.2023 |
|---|
| Publication date: | 28.12.2023 |
|---|
| Publisher: | Chair of Production Engineering (CPE), University of Maribor, Faculty of Mechanical Engineering |
|---|
| Year of publishing: | 2023 |
|---|
| Number of pages: | str. 501-511 |
|---|
| Numbering: | Vol. 18, no. 4 |
|---|
| PID: | 20.500.12556/DKUM-87711  |
|---|
| UDC: | 681.5:004.42 |
|---|
| ISSN on article: | 1854-6250 |
|---|
| COBISS.SI-ID: | 182007555 |
|---|
| DOI: | 10.14743/apem2023.4.488 |
|---|
| Copyright: | Content from this work may be used under the terms of the Creative Commons Attribution 4.0 International Licence (CC BY 4.0). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. |
|---|
| Publication date in DKUM: | 25.03.2024 |
|---|
| Views: | 492 |
|---|
| Downloads: | 44 |
|---|
| Metadata: |    |
|---|
| Categories: | Misc.
|
|---|
|
:
|
Copy citation |
|---|
| | | | Average score: | (0 votes) |
|---|
| Your score: | Voting is allowed only for logged in users. |
|---|
| Share: |  |
|---|
Hover the mouse pointer over a document title to show the abstract or click
on the title to get all document metadata. |
