Statistical analysis of iron concentrate quality data
by Xiaomin Xu; Kewei Wu
International Journal of Data Science (IJDS), Vol. 7, No. 2, 2022

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.

Online publication date: Wed, 09-Nov-2022

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Data Science (IJDS):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com