PRODUCTION OF ZERO DEFECT (ZD) SLABS THROUGH THE IMPLEMENTATION OF SMART MANUFACTURING TECHNOLOGIES IN STEEL CONTINUOUS CASTING
Project Lead: ArcelorMittal
Partners: Purdue University, Missouri University of Science & Technology, Rensselaer Polytechnic Institute
Problem Statement: Absence of predictive maintenance and real-time quality prediction tools increases the overall energy intensity of the steelmaking process via increased unplanned turnarounds (UPTA) and product defects.
Project Goal: Improve steel slab quality and continuous caster productivity using Smart Manufacturing (SM) methodologies and technologies to address the top two KPIs of the continuous casting process –yield (minimize defects/rejects) and uptime (reduce UPTA).
Employ the CESMII-based SM/big-data platform to capture process and quality data
Extend and scale-up the in-house caster condition monitoring application “Caster Health Monitor” (CHM) into this new SM platform for predictive tools
Develop real-time hybrid predictive models for slab defects and quality using the SM platform
Build an interactive, SM-platform-tethered, VR-based interface of a digital twin prototype of the continuous casting process for shop-floor deployment by integrating all the above developments
Define CESMII-directed platform specification (M3)
Configure CESMII-based SM PlatformTMfor project use (M9)
Implement and prove effectiveness of new advanced sensors in the pilot caster (M12)
Extend, scale-up and demonstrate a first running version of CHM application on the new SM PlatformTM(M15)
Complete, deliver and validate an enhanced version of the CHM application as a true predictive maintenance tool (M21)
Deliver a hybrid (data-driven/machine learning based + physics-based such as CFD) slab quality prediction model (M24)
Deliver and deploy a first version of a digital twin of the pilot caster on the shop floor (M24)
A 0.2% savings in yield (from reduction of defects) is equivalent to an annual savings of $90M for the whole US steel industry (plus 2.68 PJ of energy savings per year equivalent to about 22 million gallons of gas savings, enough to power ~ 70,000 typical American homes for a year).
Predictive maintenance tools alone could save at least $2M per caster strand per year (there are hundreds of strands in the US)
Benefit to CESMII:
Transversal application of the developed technologies (available as SM Apps from the SM Marketplace) from this project would impact numerous other industries faced with similar problems and challenges
The outcome of this project is expected to trigger a paradigm shift (e.g., from quality-by-inspection to quality-by-design) in the current manufacturing practices of how preventive maintenance is done, how product quality is looked at and how dispositioning of products is performed in real time
Project Cost Share and Duration:
Project Duration: 24 months, CESMII Cost Share: 69%, Member Cost Share: 31%