The thesis is about improving the quality of steel and optimizing the cost of the secondary steel making process. It tried to examine how sensors can be useful in automating the steel production operations. The work showed that an accelerometer and a microphone which measure sound and vibration signals respectively may greatly help in estimating the actual phenomenon happening during steelmaking. The study aimed at addressing an industrial problem on accurately evaluating the volumetric gas flow rate used to mix the molten steel. The outcome of this research is used to improve steel quality.
Copyright © 2017 Jaefer Yenus.
A dissertation submitted for fulfillment of the Degree of Doctor of Philosophy, Swinburne University of Technology, 2017.