A data-mining technology for tuning of rolling prediction models: Theory and application

Abstract

The realization of physical modeling of the rolling process is proposed as a material hardness virtual sensor and represents a valid tool for data exploration. The use of unsupervised clustering technology is here proposed and explored so as ease the material grouping process that might be strictly required for technological maintenance purposes.