As steel industry margins continue to shrink, one promising way for manufacturers to increase profitability is to pursue more advanced, high-strength steel production for applications such as automotive and electrical. However, production of these advanced steel grades requires much tighter control of the overall production process, which is impacted by numerous parameters across the mill.
The MPV application utilises artificial intelligence and machine learning to create a unique ‘sense, predict, and recommend’ framework that addresses challenges associated with the variability of mechanical properties in steel production. Mechanical properties include things such as yield strength, tensile strength, and elongation.
The application senses patterns within mill data to fully understand the drivers of mechanical property variability. It then predicts when increased variability will occur and recommends the optimal input parameters, or PDI (Process Data Inputs) settings, required to optimise target mechanical properties such as yield strength, tensile strength, and elongation.
As a result, the MPV application can help steel manufacturers achieve cost savings three ways: by reducing mechanical properties variability, reducing alloy costs due to better variability control, and minimising out-of-spec production, which are sold as secondary grades or scrapped. One steel manufacturer using MPV is anticipating savings two million US dollars per year.
“Our ability to deploy AI to produce steel with tighter tolerances allows us to address the requirements of high margin segments such as automotive and electrical, which immediately impacts our top line revenues in addition to the obvious cost savings,” said Denis Hennessy, Director of Product Development at Big River Steel, after implementing the MPV application.
In addition to addressing these challenges in mechanical properties variability, the AI and machine learning solutions that Noodle.ai and SMS digital have co-developed will also help steel manufacturers optimise product quality, asset availability and production efficiency. Together, Noodle.ai and SMS digital combine manufacturing equipment expertise, process modeling experience, and cutting-edge data science to accelerate time to value, enabling customers to quickly realise bottom-line impact.
“This partnership with SMS digital was created to make efficiency improvements that not only help steel manufacturers’ bottom line, but to rid the world of unnecessary industrial waste that often plagues this industry,” said Stephen Pratt, Founder and CEO, Noodle.ai. “We are encouraged by the results we’ve already seen with this application developed in partnership with SMS digital, and anticipate being able to assist an even larger list of steel manufacturers as we enter 2020 with MPV and the other applications we develop together.”
_{(Source: SMS group)}