Analysing Sintering Performance by Data Mining
BlueScope Steel restructured its Port Kembla primary operations in late 2011 which included the shutdown of one blast furnace and a reduction in the targeted productivity of the sinter plant Concurrently,the blast furnace ferrous feed shifted from a lump/pellet/sinter mix produced from Australian and Brazilian iron ores to a lump/sinter burden with the lump ore and sinter produced from Australian and New Zealand ores.This led to significant changes at the sinter plant and blast furnace,which shifted both processes towards relatively new operating regimes.While adapting to the new process conditions has presented some challenges,it also presents an opportunity to analyse a single plant with a significant change in its operation.Data mining techniques were used to investigate relationships between sinterfeed blend,sinter quality and BF performance during this period.These techniques offer powerful analytical processes for characterising complex multivariate systems and identifying causality while minimising bias in the analysis.Although accumulation of a sufficiently large data set with the new operating conditions is continuing,the preliminary analysis presented is promising.
data mining sinter blast furnace
David Pinson Andrew Gadd
Steelmaking Technology and Planning, BlueScope Steel, Australia David Technical Marketing, Iron Ore, BHP Billiton, Singapore
国际会议
The 4th Australia-China-Japan Joint Symposium on Iron and Steelmaking(第四届中日澳钢铁冶金学术会议)
沈阳
英文
32-37
2012-11-03（万方平台首次上网日期，不代表论文的发表时间）