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EAST Session:

EAST Session: Moderated by: Steve Plumb Rather than start with a discussion of all the technologies available in the industrial marketplace, this panel session will start by outlining the primary concerns of manufacturing businesses. By first appealing to what the audience (machining businesses) cares about most at the start, the panel will logically ease into a discussion of how available technologies can help achieve greater outcomes for these businesses…in other words, solutions to the preeminent problems. Among the concerns highlighted at the outset will be improving competitiveness (domestically and globally), throughput (business growth), and yes productivity in the face of the manufacturing skills gap. The panel will be represented by industry leaders who either are dealing with these concerns directly, or those that have a “front row seat” to a variety of companies that seek to survive and thrive. Technologies that will be addressed will likely include automation, robotics, workforce training, machining technology, machine monitoring, software and AI to name a few. The above will be discussed in the first Executive Perspectives panel discussion on Tuesday, followed on Wednesday with another critical topic…cybersecurity.

Speaker at EAST: Todd Basque, Director of Engineering, Basque Engineering + Science Inc.

Speaker at EAST: Ryan Benson, Vice President of Security, CompassMSP

Speaker at EAST: Tiansu Jing, Senior Product Manager, SIEMENS Industry Inc.

Speaker at EAST: Gavin Giguere, Director of Manufacturing | Vice President, Pilot Precision Products | Western MA National Tooling and Machining Association

EAST Session:

EAST Session:

EAST Session:

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.