Monday, 7 October 2024

4–6 p.m.

Registration

Tuesday, 8 October 2024

7 a.m.

Registration and Breakfast

7:50 a.m.

Opening Remarks

8 a.m.

Keynote: Enabling Industry 4.0 in the Steel Industry: An Integrated Approach to Overcome ROI Hurdles and Effectively Drive Performance
Thiago Turchetti Maia

8:50 a.m.

Building Industrial-Grade AI in the Steel Industry
Chris Conry, The RoviSys Co.
Artificial intelligence (AI) and machine learning (ML) has been dominating media and conversations at every company and across the globe. Practical applications that make an impact can be difficult to discover and commission. This presentation will walk through different types of machine learning. Whether it's supervised learning to predict the lifetime of a caster segment, unsupervised learning providing insight to reheat furnace operators, or reinforcement learning scheduling material transfers across the site, this presentation will share strategies to target use cases, mitigate risks and make successive projects more successful.

9:25 a.m.

Break

9:40 a.m. 

Enhancing Manufacturing Execution Systems With Artificial Intelligence: A Collaborative Framework for Process Optimization
Luc Van Nerom, PSI Metals North America Inc.
This presentation will discuss the application of artificial intelligence (AI) in manufacturing execution systems (MES). By leveraging AI's predictive capabilities, MES systems can proactively identify potential production disruptions, enable timely process intervention, reduce quality failures and minimize downtime. The collaboration of MES and AI frameworks represents a transformative step toward achieving Industry 4.0 principles. By harnessing the strengths of both technologies, steel producers can achieve unprecedented levels of operational excellence, quality and responsiveness.

10:15 a.m. 

Multitool Robot for Caster Operations
Gianluca Maccani, POLYTEC USA
Smart industrial robots are revolutionizing casting operations by handling the most dangerous tasks, including lance manipulation, ladle shroud sampling, measurement and powder distribution. These robots are being implemented across multiple locations in North America. This session will present the latest developments in these technologies.

10:50 a.m. 

Accelerating Steel Alloy Development Through Microstructural Knowledge Discovery
Patrick Cleaver and Malavikha Rajivmoorthy, Cleveland-Cliffs Research & Innovation Center
Materials discovery of steel alloys relies on microscopy to inform metallurgists of structural characteristics, which are determined by processing history and result in material properties. This session will present a processing method of digital micrographs to obtain salient microstructural features via spatial statistical methods. Two case studies will be reviewed — one assessing a dual-phase steel processing route with supplementary through-coil structural data based on magnetic induction, and the other depicting the real-time determination of the degree of grain recrystallization directly influencing mechanical properties in high-strength, low-alloy steels via pyrometry.

11:25 a.m.

Lunch

12:30 p.m. 

Keynote: Industrial AI: Solving the Unsolvable Problems
Bryan Debois, The RoviSys Co.
Autonomous AI represents an inflection point in industrial AI. Autonomous AI is a methodology, not a product, and it allows training of neural network "brains" that can make optimal decisions even in the face of novel situations. While relatively new, it has been used by industrial companies for everything from adjusting moisture content in sausages, to shaping of glass bottles, to production scheduling in paint manufacturing. This presentation will discuss real-world examples where autonomous AI has been deployed in industrial settings to solve previously unsolvable problems.

1:20 p.m.

Leveraging Computer Vision to Improve Production Safety
Dante Vaccaro, Schneider Electric
Computer vision is revolutionizing safety in the steel industry, offering real-time monitoring and instant deviation alerts. This presentation will discuss how this innovative technology can ensure that proper safety equipment is used and operator tasks meet stringent safety standards, while also paving the way for automated inspections and continuous improvement.

1:55 p.m.

Break

2:10 p.m.

Leveraging AI Insights for Effective Condition-Based Maintenance (CBM)
Suhas Mehta, Falkonry
Despite the undeniable advantages offered by the condition-based maintenance (CBM) approach, the adoption of CBM in steel manufacturing faces challenges due to the unavailability of curated data and the need for more proficiency in setting up the conditions for every piece of equipment. As a result, the scope of CBM coverage is limited and maintenance practices are largely reactive, leading to several hours of lost productivity due to manual and intuition-based root cause analysis and recovery actions. This presentation will discuss leveraging automated AI analysis of raw time series data from programmable logic controllers and sensors to perform live monitoring of steel equipment and processes. By combining AI insights and conditional rules engine, subject matter experts can create a robust monitoring system that triggers actions appropriate for a given condition. Practical use cases of deploying this condition-based approach at the line scale in steelmaking operations will also be presented.

2:45 p.m.

Optimizing Electric Arc Furnace Performance via Deep Learning–Driven Sidewall Temperature Forecasting
Sebastian Schreiber, SMS Group

3:20 p.m.

Break

3:40 p.m.

Safety and Digitalization Technologies Panel Discussion
Panelists:

• Pinak Dattaray, Ripik AI
• Alacyia Fields, Nucor Steel-Lexington
• Garrett Urie, Stelco Inc.

5:05 p.m. 

Reception

Wednesday, 9 October 2024

7 a.m. 

Breakfast 

8 a.m.

Keynote: Digitalization: The Gateway to Innovation and Discovery
Sunday Abraham, SSAB Americas
Digitalization can play a significant role in transforming a business into a more efficient and cost-effective organization. While analog systems provide an overall picture of a process, digitalization leverages digital technologies for discrete and quantitative assessments of process phenomena. In this context, digitalization can be regarded as the gateway to innovation and new discovery. In this keynote lecture, examples will be given of how digitalization led to quality improvement and process optimization at SSAB Americas.  

8:50 a.m.

Break

9:05 a.m.

Predictive Maintenance Panel Discussion
Moderator:
Panelists:

• Bryan DeBois, RoviSys
• Dante Vaccaro, Schneider Electric
• Suhas Mehta, Falkonry

10:35 a.m.

Break

10:50 a.m.

QQC-1: A Self-Learning Multiagent AI Framework for Real-Time Classification, Search and Reasoning of Metal Defects
Yousef Mohassab, Facilis.ai
Traditional defect detection and classification methods often fall short in speed, accuracy and explainability when deployed in production. To address these challenges, QQC-1 (Quanta Quality Control-1) will be introduced. QQC-1 is an adaptive AI multiagent framework designed for real-time classification, search and reasoning of metal defects. QQC-1 utilizes cutting-edge AI algorithms to achieve superior speed, precision, explainability and self-learning capabilities for metal defect applications. 

11:25 a.m. 

Harnessing Energy Consumption Insights for Enhanced Production Efficiency in Steel Manufacturing
Manko Ho, iba America

Noon

Lunch

1 p.m.

Keynote:  Digital Transformation for Ironmaking: An Integrated Virtual Blast Furnace for Operational Guidance and Process Improvement
Tyamo Okosun, Purdue University Northwest

1:50 p.m.

A Practical Application to Machine Learning in Machine Predictive Maintenance

2:25 p.m.

AI in Steel Today: Lessons Learned and Why You’re Missing Out
Matthew Mathes and Kervin Blanke, Metallus Inc.

3 p.m.

Break

3:15 p.m. 

Producer Panel Discussion
Nathan Settlemire, Charter Manufacturing Co.   

5 p.m.  

Conference Adjourn