A Smart Maintenance tool for a safe Electric Arc Furnace

摘要

The production process in steel making involves plenty of variables to know the actual status in plant operations and the deviations from optimal and safe operating conditions. The deviations depend on diverse uncertainties due to the material variability and, more in general, the complexity of modeling the physical and chemical transformations occurring in the production assets. The transformations are partially observable by means of measurable parameters. The "man in the loop" is then essential to cope with the tasks of monitoring, controlling and diagnosing the asset health status. Today, these tasks can be aided by the plant automation as a lever to support supervision and decision by the operators. The project reported by this paper was developed in this context, leading to enhance the decision-making capabilities. In particular, a condition monitoring tool was deployed by seeking the opportunities provided by plant automation enhanced according to Industry 4.0 paradigm. The tool is now running on an Electric Arc Furnace of the steel making plant of Tenaris Dalmine, in Italy. The project used the experience and knowledge gained by Tenaris Dalmine process and maintenance operators as foundation for initiating the conceptualization of a novel and approach. Thus, the tool - resulting from engineering and implementation of the concept - is integrating plant automation with intelligent data analytics, as a result of close collaboration between Tenaris Dalmine and the Manufacturing group of the Department of Management, Economics and Industrial Engineering of Politecnico di Milano. The tool enables to detect incipient failures through monitoring of the furnace panels and of the hearth/bottom of the furnace; thus, it allows to enhance the operations by avoiding downtimes that may lead to risky consequences on people safety. The tool has to be considered an example of smart maintenance and its implementation reflects a path towards building cyber-physical systems in production.