Date/Time
Date(s) - 09/18/2024
5:30 pm - 8:00 pm
Categories
Are You Ready for AI ?
Some simplified views of AI and issues to consider in order to exploit AI technologies at your facility.
James Wiczer, PhD, Sensor Synergy, Inc., Vernon Hills, Illinois
Location:
American Foundry Society, Inc.
1695 N Penny Ln, Schaumburg, IL 60173
Agenda:
5:30 PM Check-In & Networking
6:00 PM Dinner
6:30 PM James Wiczer’s Presentation.
On the Menu:
Classic Chef’s Table
- Parmesan Panko-Crusted Chicken with White Wine Reduction Sauce
- Sliced Sirloin of Beef with Creamy Horseradish and Au Jus Ctil’i
- Lemony Angel Hair Pasta with Artichokes
- Parmesan Garlic Roasted Potatoes Ctil’i
- Steamed Green Beans with Brown Butter and Almonds Ctil’i Candled Walnut and Cranberry Spring Salad Ctil’i with Sweet Poppy Seed Dressing
- Fresh Baked Rolls and Butter
- House made Fudge Brownies
- Assorted Beverages
Registration Deadline: Noon, Friday, September 13th
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About the Presentation:
Dr. Wiczer will discuss approaches to measuring key parameters and will highlight the potential for applying both AI and human intelligence to “real-life” issues in metal casting operations.
“AI“– the shorthand notation for the term Artificial Intelligence, may be the biggest marketing bonanza since the phrase “the Web.” Without question, AI will have a large impact on all of our futures from helping make better product in our foundries to reminding us to take the correct pill in the morning while an AI powered android Robot helps us get out of bed in the morning at our Assisted Living facilities. Leaving that image for a future discussion, consider a simplified way to think about AI.
In fact, we can think about AI in 2 broad categories – Generative AI and Predictive AI.
Both use machine learning, pattern recognition, vast amounts of training data, and a wide range of other software and hardware tools developed to help AI system do more. In the simplest case, we can think of Generative AI as creating (almost) unique types of content from impressively detailed artwork to stories about how I spent my summer vacation.
Predictive AI identifies patterns in related, prior data (training data) and tries to predict when an event will occur in the future. For example, “based on current and prior measurements of furnace properties, when will this furnace need to be refurbished?” or “how can I adjust the injection rate to reduce defects?” In the simplest case, to utilize predictive AI in foundry operations, process data and product quality data must be collected and correlated so that AI compute engines can identify patterns.
Before exploring the details of AI implementation, it is important to identify the potential benefits from augmenting a production process with AI and understanding the economics. In particular, the potential value of the yield improvement (or other enhancement) must significantly exceed the cost of implementing an AI system. If the product run is relatively small and the yields are already relatively high, you may not be able to improve yields enough to justify the cost of the AI system – especially the cost of preliminary data collection and the training necessary to establish an AI solution.
AI systems need to correlate changes in processes with changes in product quality; this may require serializing products so that retrospective correlations of process parameters with product quality will be possible.
The key parameters affecting product quality may not be measured in your existing process; this may necessitate changes in your production process to measure the required control setting or physical parameters.
About the Speaker:
James (Jamie) Wiczer earned his BS degree in Electrical Engineering from Purdue University in W. Lafayette, IN in 1972 and 4 years later his PhD in Electrical Engineering from the University of Illinois at Champaign-Urbana, IL.
Jamie followed his PhD work with an 18-year tenure at Sandia National Labs in Albuquerque, NM as a staff member, division supervisor and department manager. After his work at Sandia Labs, Wiczer focused his efforts on developing and promoting the practical applications of networked, smart sensor technologies in order to make manufacturing and other industrial operations more cost effective and globally competitive.
In 1999, he founded, and currently serves as president of Sensor Synergy, a US-based developer of Internet-based, industrial monitoring solutions for improved energy efficiency and productivity. Wiczer has published over 80 articles on his research and development work, has been awarded seven patents on sensors and sensor interfaces and was awarded the prestigious American Foundry Society “Applied Research Award” for his efforts to reduce energy consumption in metalcasting foundries. He is a member of the IEEE, American Foundry Society, Tau Beta Pi, HKN and other professional organizations. Jamie provides lectures to local high schools and junior high schools about engineering career opportunities. Wiczer also has served in various capacities to support the Illinois Junior Academy of Sciences and their annual science fair programs.
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