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EAST Session: Effective data collection is critical for optimizing production lines, yet traditional methods such as manual recording and PLC-coded data collection are fraught with inefficiencies and inaccuracies. Manual data entry often misses short downtime events and is subject to operator bias, while PLC-based systems suffer from inconsistencies, excessive costs, and revalidation challenges. The future of data collection lies in automation, modular modeling, and intelligent data processing, providing a foundation for digital transformation and sustainable manufacturing excellence. This session will explore the following concepts: · Advanced data collection goes beyond monitoring bottleneck operations, incorporating machine-level insights across all assets. · A multi-layered approach – integrating real-time signal processing, logic engines, and high-speed data acquisition – enhances fidelity, reduces integration costs, and improves root cause analysis. · Additionally, Aa Fault Learning approach dynamically identifies and ranks faults, leading to better diagnostics and predictive maintenance. · By leveraging digital twins, synchronizing multiple data streams, and enabling fast data validation, companies can significantly improve operational efficiency. · A robust data collection strategy supports MES, OEE, and AI/ML applications, ensuring accurate modeling, predictive analytics, and enterprise-wide standardization.

EAST Session: Industrial AI is more accessible than ever. This technology, long viewed as “too complex” to implement, is now a practical productivity accelerator for manufacturers. The complexity misconception stems, in part, from the thinking that integration requires tearing out current systems. However, the reality is that it’s easily compatible with most legacy systems. By layering Industrial AI, ML, and other complementary tools on top of this existing data infrastructure, manufacturers reveal new improvement areas and free key resources to focus on the work that dictates long-term success. In this session, you’ll see how Industrial AI turns today’s operational challenges into an opportunity, a springboard for growth, and a means to provide your people with essential solutions. With capabilities like real‑time data contextualization and prescriptive recommendations, Industrial AI helps: - Make smarter decisions faster - Deliver continuous, measurable value - Scale subject matter expertise enterprise-wide Join us to learn how Industrial AI amplifies your workforce, maximizes the potential of your operations, and moves it forward faster than ever.

EAST Session: Abstract : As factories and job shops move towards Industry 4.0, machine tools are becoming more connected, opening up new possibilities for productivity and efficiency. However, this connectivity also brings new cybersecurity risks. Many manufacturers think cybersecurity is just an IT issue, but the reality is that the shop floor is now a prime target for cyberattacks, ransomware, and system breaches that can halt production and damage equipment. In this session, we'll dive into practical, actionable strategies to boost cybersecurity specifically for machine tools and manufacturing systems. You'll learn why modern CNC machines, robots, and connected equipment are at risk, discover common vulnerabilities in connected manufacturing environments, and explore cost-effective cybersecurity best practices tailored for small and medium manufacturers. We'll also discuss how to collaborate with machine builders, software providers, and integrators to build resilient systems, share real-world case studies of attacks and lessons learned, and outline key steps you can take today to reduce risk without slowing down production. Whether you're running a high-mix job shop or a high-volume plant, this session will help you understand cybersecurity from the perspectives of operators, plant managers, and owners, and provide you with a roadmap to protect your business as you modernize operations. Significance/Importance : This presentation is crucial because it equips manufacturers with practical strategies to protect their connected systems from cyber threats, ensuring productivity and safety as they embrace Industry 4.0. Additionally, it will help the shop owner to be compliant with the cybersecurity requirement from the U.S. Deportment of Department of Defense (DoD) and European regulations.

EAST Session: Abstract : In today's highly competitive manufacturing landscape, operational efficiency is more critical than ever. Yet, excessive energy consumption and unplanned downtime remain major challenges, significantly impacting productivity and costs. Traditional maintenance strategies often fail to address the root causes of inefficiencies, leading to unnecessary energy waste and unexpected failures. This session explores Energy-Centered Maintenance (ECM)—a data-driven, AI-powered approach that goes beyond conventional reliability-centered maintenance by integrating energy efficiency as a key decision-making factor. By leveraging advanced IoT sensors, AI-driven analytics, and real-time machine health monitoring, manufacturers can proactively detect faults, minimize energy loss, and extend asset life. Through real-world case studies and industry insights, attendees will learn how ECM enables manufacturers to reduce operational expenses, prevent unplanned downtime, and achieve sustainability goals—all without compromising productivity. The session will also highlight how machine learning and AI-driven predictive analytics help manufacturers make smarter maintenance decisions, optimizing energy use while ensuring equipment reliability. Whether you're looking to cut energy costs, enhance machine uptime, or align with Industry 4.0 and sustainability initiatives, this session will provide practical takeaways to help you transform your maintenance strategy. Significance/Importance : Learning Objectives Understand the limitations of traditional maintenance strategies and how excessive energy waste and unexpected downtime impact manufacturing costs and efficiency. Explore the principles of Energy-Centered Maintenance (ECM) and how AI-driven predictive analytics can optimize machine performance, reduce energy waste, and prevent costly breakdowns.

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EAST Session: Show Floor: 9:00 AM - 5:00 PM

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Speaker at EAST: Brian Richmond, Chief Revenue Officer, Nanoprecise SCI Corp

Speaker at EAST: Eric Swezey, Senior Enterprise Account Executive, Zoovu