Effective real-time monitoring is crucial for modern iron and steel operations to prevent issues like cold furnaces or unscheduled shutdowns, which leave signatures in high-volume real-time data. Conventional monitoring often misses these signs.
Artificial intelligence enhances our ability to detect these signatures, helping to avoid lost production, improve quality, and increase campaign duration. Effective AI must offer significant avoidance opportunities, require minimal attention from operations and maintenance, and cover most operational issues to gain trust and advance digital manufacturing. Therefore, measuring and communicating this effectiveness is vital for digitalization in the steel industry.
This paper introduces a new metric for judging the effectiveness of real-time monitoring in digital transformation projects, regardless of the technology. We illustrate this metric with multiple real-world case studies of Time Series AI platforms applied by steelmakers globally.
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