Displaying 391-400 of 922 results for

EAST Session: Abstract : Manufacturers have more customer data than ever before, yet many still struggle to turn that data into real insights. Too often, sales teams rely on gut instinct, outdated reports, or incomplete CRM entries, leading to missed opportunities and inefficient processes. AI changes the game by analyzing patterns humans can’t see, uncovering hidden sales opportunities, and predicting customer needs before they arise. In this session, we’ll explore how AI can transform the way manufacturers understand and engage with customers—without requiring a complete digital overhaul. We’ll discuss real-world applications of AI in sales and customer relationships, including proactive recommendations, automated data capture, and predictive insights. You’ll leave with a clear understanding of how AI can help you move beyond guesswork, make data-driven decisions, and build stronger, more profitable customer relationships. Significance/Importance : Manufacturers have long relied on relationships and gut instinct to drive sales, but today’s competitive landscape demands more. Traditional CRMs were meant to help but became data-entry burdens, leading to poor adoption and missed opportunities. AI is changing the game by turning raw data into actionable insights—automating manual processes, predicting customer needs, and uncovering hidden sales opportunities. Companies that embrace AI gain a competitive edge, while those that don’t risk falling behind. This session will show how AI helps manufacturers move beyond guesswork, make smarter decisions, and build stronger customer relationships with less effort.

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.

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

Speaker at EAST: John Carpenter, Founder, Owner, President, Excellerant

EAST Session:

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

EAST Session:

EAST Session: Abstract : Enterprise-scale manufacturers continue to expand the use of precise 3D data and connected annotations, called Model-Based Definition (MBD), in place of traditional engineering drawings. The extent to which downstream suppliers are able to respond effectively to this ongoing, cross-industry change will be a significant determining factor on the structure of the manufacturing supply change in future decades. Guidelines from the United States Department of Defense (DoD) are major agents for change in this process. The DoD recognizes that MBD's capacity to support interoperable reuse of data across multiple production systems can accelerate engineering and manufacturing, improve quality, and reduce costs. When major private sector institutions like Deloitte produce findings showing how larger enterprises can gain efficiencies through these practices, expectations grow for the downstream suppliers to align themselves to these changes. For example: Lockheed has already made public that it expects its suppliers to be able to provide inspection data generated in downstream processes to be returned to them, a level of data exchange — the Digital Thread — only possible through integrated MBD processes. Understanding the factors that are currently limiting the expansion of MBD practices, and how technologies are being deployed to overcome those limits, gives perspective to today's manufacturing supplier on how they can prepare for the most imminent developments likely to arise. Significance/Importance : Industry advancement towards model-based definition (MBD) grows with each passing day in many key industries; leading the way are aerospace and defense. Major OEM manufacturers are deeply invested in this process evolution, and there are few if any market pressures influencing factors towards any other direction. Only inertia and cost of entry are acting to constrain this fundamental change.

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: Abstract : Manufacturers are keen and pragmatic on how their capital is used to advance their state of manufacturing.  And it is clear to them how investments in physical assets bring operational value.  What is not so clear is the value-add of technology to their operations.  In this session, you will learn how to translate the value of technology to operations to facilitate internal planning and justification for technology investments. You will learn how to build a business case around technology to show the expected value and ROI of that investment. Using this approach, the project team can report the financial gains to key constituents to help with continued funding and support.  Significance/Importance : Manufacturers are keen and pragmatic on how their capital is used to advance their state of manufacturing.  And it is clear to them how investments in physical assets bring operational value.  What is not so clear is the value-add of technology to their operations.  In this session, you will learn how to translate the value of technology to operations to facilitate internal planning and justification for technology investments.