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Application of Innovative Methods of Predictive Control in Projects Involving Intelligent Steel Processing Production Systems
This paper describes the enhancement of the existing predictive system of quality management in the processes of metallurgic manufacturing. Specifically, it addresses steel-strip manufacturing. The main quality management innovation is the transition from the current methodological process of a sing...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8037254/ https://www.ncbi.nlm.nih.gov/pubmed/33801618 http://dx.doi.org/10.3390/ma14071641 |
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author | Svetlík, Jozef Malega, Peter Rudy, Vladimír Rusnák, Ján Kováč, Juraj |
author_facet | Svetlík, Jozef Malega, Peter Rudy, Vladimír Rusnák, Ján Kováč, Juraj |
author_sort | Svetlík, Jozef |
collection | PubMed |
description | This paper describes the enhancement of the existing predictive system of quality management in the processes of metallurgic manufacturing. Specifically, it addresses steel-strip manufacturing. The main quality management innovation is the transition from the current methodological process of a single-step defect evaluation to a two-step evaluation. A two-step defect check of the strip’s surface involves checking for defects during the hot-rolling process first, and double-checking it during the process of pickling. These defects are detected in a well-established process of camera imaging in the production process. The recorded image is then processed mathematically to find the degree of defect correlation in those processes. The two-step evaluation enables a more detailed focus on a particular defect and its position on the strip. Decisions concerning further processing are based on defect evaluation, for instance, whether a rework is necessary to maximize the product utilization and minimize the eventual negative impact of the defect on production equipment. A crucial aspect is also the reduced probability of failures in the manufacturing process. |
format | Online Article Text |
id | pubmed-8037254 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-80372542021-04-12 Application of Innovative Methods of Predictive Control in Projects Involving Intelligent Steel Processing Production Systems Svetlík, Jozef Malega, Peter Rudy, Vladimír Rusnák, Ján Kováč, Juraj Materials (Basel) Perspective This paper describes the enhancement of the existing predictive system of quality management in the processes of metallurgic manufacturing. Specifically, it addresses steel-strip manufacturing. The main quality management innovation is the transition from the current methodological process of a single-step defect evaluation to a two-step evaluation. A two-step defect check of the strip’s surface involves checking for defects during the hot-rolling process first, and double-checking it during the process of pickling. These defects are detected in a well-established process of camera imaging in the production process. The recorded image is then processed mathematically to find the degree of defect correlation in those processes. The two-step evaluation enables a more detailed focus on a particular defect and its position on the strip. Decisions concerning further processing are based on defect evaluation, for instance, whether a rework is necessary to maximize the product utilization and minimize the eventual negative impact of the defect on production equipment. A crucial aspect is also the reduced probability of failures in the manufacturing process. MDPI 2021-03-27 /pmc/articles/PMC8037254/ /pubmed/33801618 http://dx.doi.org/10.3390/ma14071641 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ). |
spellingShingle | Perspective Svetlík, Jozef Malega, Peter Rudy, Vladimír Rusnák, Ján Kováč, Juraj Application of Innovative Methods of Predictive Control in Projects Involving Intelligent Steel Processing Production Systems |
title | Application of Innovative Methods of Predictive Control in Projects Involving Intelligent Steel Processing Production Systems |
title_full | Application of Innovative Methods of Predictive Control in Projects Involving Intelligent Steel Processing Production Systems |
title_fullStr | Application of Innovative Methods of Predictive Control in Projects Involving Intelligent Steel Processing Production Systems |
title_full_unstemmed | Application of Innovative Methods of Predictive Control in Projects Involving Intelligent Steel Processing Production Systems |
title_short | Application of Innovative Methods of Predictive Control in Projects Involving Intelligent Steel Processing Production Systems |
title_sort | application of innovative methods of predictive control in projects involving intelligent steel processing production systems |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8037254/ https://www.ncbi.nlm.nih.gov/pubmed/33801618 http://dx.doi.org/10.3390/ma14071641 |
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