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Multivariable data analysis of a cold rolling control system to minimise defects
Mälardalen University, School of Sustainable Development of Society and Technology.
Mälardalen University, School of Sustainable Development of Society and Technology.
Mälardalen University, School of Sustainable Development of Society and Technology.ORCID iD: 0000-0002-7233-6916
Cogent Power Ltd, Surahammars Bruk.
2011 (English)In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 54, no 5-8, p. 553-565Article in journal (Refereed) Published
Abstract [en]

This paper focuses on the application of principal component analysis (PCA) to thoroughly analyse and interpret multidimensional data from a cold rolling process. The analysis includes the effects of variables on the final properties of strips in a cold rolling mill. Unscrambler software was used to analyse and identify hidden variables. Variable correlations were also used to derive correlations between the control parameters. The results of this research will be used to improve the selection of material in order to reduce the occurrence of defects in the cold rolling process and to improve the adjustment of the set points that are performed in every pass or section of the cold rolling process. The hot rolled strips that enter the cold rolling mill are made of different materials and are produced by different strip manufacturers. Some strips break during the thickness reduction process in the cold rolling mill. This paper focuses on two possible causes of breakage: non-uniform strip material properties and failures in the rolling mill process. Two types of rolled strips (those that break and those that do not break) were compared to identify causes of breakage. The results indicate that breakages are caused by material or process failures. PCA was applied to the dataset in order to identify and analyse the relationships between the variables in the process. This information was used to interpret and diagnose the process behaviour. Swarm analysis and relating observations to process behaviour were able to distinguish between different start-up conditions, and between desirable and undesirable process conditions.

Place, publisher, year, edition, pages
2011. Vol. 54, no 5-8, p. 553-565
Keywords [en]
PCA, Analysis, Control system, Parameter, Automation, Cold rolling
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mdh:diva-15559DOI: 10.1007/s00170-010-2946-2ISI: 000290164500012Scopus ID: 2-s2.0-79955650150OAI: oai:DiVA.org:mdh-15559DiVA, id: diva2:562278
Available from: 2012-10-23 Created: 2012-10-10 Last updated: 2017-12-07Bibliographically approved

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Dahlquist, Erik

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