Statistical analysis of iron concentrate quality data

Xiaomin Xu and Kewei Wu

International Journal of Data Science, 2022, vol. 7, issue 2, 181-196

Abstract: China's steel industry is gradually converging with the international one and is becoming an important force in the international steel industry. However, there exists a big gap between the quality of China's iron concentrate and the world standard. This paper takes the iron concentrate of a mining company as the object of quality analysis and improvement. Firstly, the toxic element sulphur in iron concentrate was found, which affects the quality of smelting steel. Secondly, the multiple linear regression method was used to analyse the indexes of influencing factors, in order to find out the key factors affecting the sulphur content. Finally, the effect of sulphur content in iron concentrate was verified by a hypothesis test, and improved results were achieved.

Keywords: data of iron concentrate; statistical analysis; quality analysis; quality improvement; software analysis; multiple regression analysis; hypothesis testing. (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=126857 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijdsci:v:7:y:2022:i:2:p:181-196

Access Statistics for this article

More articles in International Journal of Data Science from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().