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SME is excited to bring about the inaugural Advanced Manufacturing Showcase at CES. SME and CTA are collaborating to highlight and promote the advanced manufacturing resources and capabilities in the US, as more global manufacturers seek to onshore and reshore their operations.

Speaker at WEST: Nat Frampton, Co-Founder, LECS Energy, LLC

Speaker at WEST: Kenneth Cowan, Vice President, Paperless Parts

Speaker at WEST: Tyler Boykin, Vice President, Orases

Speaker at WEST: Brian Ellis, Founder, Docket

Speaker at WEST: Jeffrey Fiala, President, UnDesked

Speaker at WEST: Kevin Kerston, Senior Account Executive, SugarCRM

WEST Session: This presentation challenges the prevailing narrative that manufacturing must conform to AI, proposing instead that AI must evolve to meet manufacturing's unique demands. After over a decade of attempting to transplant cloud-designed AI models into manufacturing environments, it has become clear that this approach is not practical. Rather than continuing to quotes percentages of failures, we advocate for a fundamental shift in perspective. If AI's core strength lies in pattern recognition and learning, why not leverage this capability to make AI itself more adaptable to manufacturing contexts? This talk demonstrates how AI can be redesigned to thrive in manufacturing environments through concrete examples that accelerate the development of robust, continuously learning models. We examine three critical assumptions that, when reconsidered, significantly enhance AI adoption and scalability in manufacturing. First, we start with quantifying success. Time invested in understanding and quantifying the trade-offs that matter to a production line is invariably worthwhile. Consider quality control as an example: should you prioritize developing a model that catches every defect, or one that minimizes false positives by avoiding the misclassification of good products as defective? Like human decision-making, AI systems will inevitably make errors—the key is to design systems that account for and manage these errors rather than pretending they won't occur. Second, we tackle data strategy. Manufacturing data represents valuable intellectual property that demands strategic handling. Contrary to popular belief, more data doesn't always yield better results. Our experience shows that indiscriminate data usage often produces sluggish, costly models that are challenging to troubleshoot and maintain. Hence, data selection strategies play a crucial role in the long-term success of a solution. Finally, we emphasize AI's inherently non-deterministic nature. Treating AI as a deterministic tool fundamentally limits its adaptive potential. Instead of rebuilding AI systems with every product change, we propose designing solutions that inherently evolve with environmental shifts—both incremental and substantial. This approach positions AI as a dynamic partner in manufacturing, capable of continuous learning and adaptation rather than a rigid tool requiring costly reconfiguration.

WEST Session: Your next efficiency breakthrough isn't hiding in a machine learning algorithm. It's walking around your shop floor right now. While manufacturing obsesses over AI, 85% of operations still depend on human expertise. The CNC programmer who knows exactly when to adjust spindle speeds. The veteran welder who spots perfect joints in seconds. The setup technician whose alignment cuts cycle times. These operators don't just run your processes, they've mastered them. They hold the institutional knowledge that separates good production from great production. But your systems can't see what they know, creating a costly blind spot. Mid-market manufacturers nationwide face the same challenge: valuable knowledge trapped in individual heads instead of being scaled digitally. The result is lost efficiency because operator expertise can’t integrate with core systems. Companies overcoming this aren’t layering more machine learning. They’re building systems that amplify human intelligence. They digitize workflows, connect teams to real-time data, and create interfaces designed around how operators think and work, not the other way around. In this session, Docket will reveal how shop floor digitization platforms close the gap between operator expertise and digital execution. You’ll gain practical insights into smart manufacturing systems that support your frontline, enabling faster setups, higher accuracy, and smoother production. At a time when manufacturers chase the next big overhaul, don’t overlook the team that got you here. The goal isn’t replacing human insight, it’s designing systems that can multiply it.