z-logo
open-access-imgOpen Access
Optimal batching plan of deoxidation alloying based on principal component analysis and linear programming
Author(s) -
Zinan Zhao,
Shijie Li,
Shuaikang Li
Publication year - 2020
Publication title -
journal of mechanical engineering research
Language(s) - English
Resource type - Journals
ISSN - 2630-4945
DOI - 10.30564/jmer.v3i2.1903
Subject(s) - deoxidization , constraint (computer aided design) , dimension (graph theory) , linear programming , principal component analysis , yield (engineering) , process (computing) , component (thermodynamics) , mathematical optimization , plan (archaeology) , principal (computer security) , function (biology) , computer science , process engineering , engineering , mechanical engineering , mathematics , materials science , metallurgy , physics , artificial intelligence , pure mathematics , thermodynamics , operating system , history , archaeology , evolutionary biology , biology
Article history Received: 21 May 2020 Accepted: 21 May 2020 Published Online: 31 May 2020 As the market competition of steel mills is severe, deoxidization alloying is an important link in the metallurgical process. To solve this problem, principal component regression analysis is adopted to reduce the dimension of influencing factors, and a reasonable and reliable prediction model of element yield is established. Based on the constraint conditions such as target cost function constraint, yield constraint and non-negative constraint, linear programming is adopted to design the lowest cost batting scheme that meets the national standards and production requirements. The research results provide a reliable optimization model for the deoxidization and alloying process of steel mills, which is of positive significance for improving the market competitiveness of steel mills, reducing waste discharge and protecting the environment.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom