Artificial intelligence, Machine Learning, and Big Data are transforming manufacturing operations in virtually every industry. This panel discussion will feature experts presenting case studies, ROI, and lessons learned.
Moderated by Cindy Tomei, CAE, VP Membership Growth & Engagement, Illinois Manufacturers’ Association
The Future Car Factory – How AI Can Prevent the $22 Billion Cost of Recalls
Before making it off the manufacturing line and throughout the entire lifecycle of the car, AI has the ability to improve vehicle safety and maintenance. New AI-powered vehicle inspection systems can conduct a 360-degree scan of a car in seconds to identify potential threats and anomalies. Using computer vision and machine learning technology, manufacturers can scan the undercarriage, body and tires of a car to find wear and tear, malfunctions and even bombs. AI-based scanners can be used not only by auto manufacturers on the assembly line, but also by used car sales, rental car companies, government offices, embassies and many others to ensure the safety of vehicles. Auto OEMs like ŠKODA AUTO are using AI systems to scan vehicles before leaving the manufacturer to prevent recalls, an industry-wide issue that costs $22 billion.
Ilya Bogomolny, Deep Learning Team Lead • UVeye
Industry 4.0 for Pulp-and-Paper Industry
Pulp-and-paper is a continuous manufacturing process. Any out-of-specification production is
difficult to detect and prevent in real-time. This causes losses in the order of millions of dollars
for a paper mill. Additionally, on average one paper break (the paper reel tearing during the
production) can occur every day on a machine. Typically breaks add about $6 to $8 million loss per
year for a mill. These costs can be reduced by deploying an Industry 4.0 AI and predictive
analytics system at the mill.
Chitta Ranjan, Director of Data Science • ProcessMiner
Creating Autonomous Chemical Plants of the Future
Chemical manufacturers who are facing increased pressure to optimize costs and gain higher yields, while simultaneously improving quality and reducing emissions, can now turn to AI-driven automation for key asset and process operations. Hear about the mainstream accessibility of artificial technology among chemical plants, and how such accessibility has the power to impact everything from process advisory to autonomous operations.
Prabal Acharyya, Head of Industrial AI • Petuum