Data-based process monitoring, process control, and quality improvement: Recent developments and applications in steel industry

Abstract

The issue of how to improve product quality and product yield in a brief period of time becomes more critical in many industries. Even though industrial processes are totally different in appearance, the problems to solve are highly similar: how to build a reliable model from a limited data, how to analyze the model and relate it to first principles, how to optimize operating condition, and how to realize an on-line monitoring and control system and maintain it. In this paper, statistical process monitoring and control methodologies are briefly surveyed, and our application results in steel facilities are presented. The achievements of the present work are as follows: (1) the development of a new method that can cope with qualitative quality information and relate operating conditions to product quality or product yield, (2) the simultaneous analysis of multiple processing units including a converter, a continuous caster, a blooming process, and rolling processes, and (3) the successful application results in the steel industry.