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WEST Session: In this presentation, we’ll explore how GibbsCAM empowers modern machine shops to overcome complex manufacturing challenges through advanced, yet intuitive, CAM technology. We’ll walk through real-world part examples that demonstrate how GibbsCAM streamlines programming for Milling, Turning, and Multi-Task Machines. Attendees will learn how to reduce cycle times, improve toolpath quality, and eliminate redundant operations using intelligent automation, toolpath optimization, and post processor customization. We’ll highlight strategies like adaptive roughing, simultaneous machining, and sync management for multi-channel machines—all designed to help manufacturers maximize spindle uptime and shorten setup times. We'll also showcase how GibbsCAM’s associative modeling, geometry creation tools, and integrated simulation reduce scrap and improve confidence before the part hits the machine. This session will provide actionable insights to improve programming workflow. By combining powerful functionality with a user-friendly interface, GibbsCAM gives you the control and flexibility needed to stay competitive in today’s fast-paced manufacturing world. Join us to see how GibbsCAM can help you do more with your machines.

WEST Session: Scaling Hardware Without the Headaches: The Critical Need for Automated Procurement Technology Hardware manufacturing teams face unprecedented challenges in scaling procurement operations while maintaining speed, compliance, and cost efficiency. Electronic components represent 70% of the bill of materials in mission-critical industries, yet traditional procurement systems rely on manual processes that create bottlenecks and force engineering teams to spend valuable time on logistics rather than core product development. The hardware industry urgently needs technological solutions that transform procurement from a laborious, error-prone process into automated workflows that scale efficiently without proportional increases in headcount. Modern procurement platforms must integrate advanced technologies to address the unique complexities of electronic component sourcing. Critical Technology Requirements: AI-Powered Process Automation - Advanced systems that can automatically parse unstructured data from supplier communications, emails, and attachments, converting them into structured data for ERP integration. Machine learning algorithms should track complete bills of materials across hundreds of suppliers, providing predictive insights and automated exception reporting to prevent supply disruptions. Intelligent Supplier Network Management - Technology platforms that leverage large databases of pre-vetted suppliers, using automated matching algorithms to connect procurement teams with suppliers based on technical specifications extracted from 2D/3D drawings and process documentation. This eliminates the time-consuming manual vetting process that often takes weeks. Real-Time Supply Chain Visibility - Integrated systems that provide instant access to inventory levels, bill of materials analysis, and global supply intelligence, with predictive algorithms that alert teams to compliance issues, supply disruptions, and component lifecycle changes weeks before they impact production. Research indicates that organizations implementing automated procurement technologies achieve 20% efficiency improvements while maintaining compliance with strict industry regulations. The future of hardware manufacturing depends on developing and adopting these technological solutions to eliminate traditional procurement bottlenecks and enable innovation in aerospace, defense, robotics, and other critical industries.

Speaker at WEST: Guillermo Peregrino, Manufacturing Engineering Manager, Aero Bending Company

Speaker at WEST: Yaron Alfi, CEO, Magenta Software, Inc

WEST Session: AI is everywhere in the headlines, but most manufacturers are still asking the same question: where do we start? Between vendor hype and uncertain ROI, it’s hard to separate what’s possible from what’s practical. This talk will help cut through the noise and share a pragmatic roadmap for building AI capability in manufacturing. Attendees will learn three proven ways to apply AI today: automating documentation, accelerating compliance, and capturing engineering expertise, along with three common pitfalls to avoid when launching AI initiatives. Rather than a futuristic vision, this session provides concrete, usable steps that any manufacturer can take immediately, whether they’re a 50-person shop or a global enterprise. The key message: you don’t need a lab full of data scientists to get started. With the right workflows, AI can deliver measurable results now, and prepare your organization for the next decade of manufacturing innovation.

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

Speaker at WEST: Jamie Goettler, Chief Revenue Officer, BTX Precision

Speaker at WEST: Luis Solano, Customer Engineering- Manufacturing Lead, Google Cloud

Speaker at WEST: Tyler Boykin, Vice President, Orases

WEST Session: Most manufacturers begin their AI journey with high expectations, yet research shows that 95 percent of GenAI projects fail to create real business value. A common trap is the shiny object syndrome, where leaders and empowered employees chase trendy tools that look impressive but do little to address core operational challenges. This is why only 5 percent of enterprise-built AI tools ever make it into production. The companies that succeed take a different path. They delve into the business itself, uncovering where AI can make the most significant difference. Predictive maintenance that prevents costly downtime, quality control that reduces waste, and supply chain optimization that improves resilience are just a few areas where measurable impact becomes possible. What often separates success from failure is expertise. Internal teams, no matter how skilled, can be limited by organizational bias, resource gaps, and familiar ways of thinking. That is why internal builds succeed only a third of the time. Third-party AI experts, on the other hand, bring fresh perspectives that identify blind spots, challenge assumptions, and apply proven frameworks that raise the success rate to nearly 70 percent. With the proper guidance, AI stops being an expensive experiment and becomes a powerful, revenue-generating asset. For manufacturers, this shift marks the difference between falling behind and building a sustainable competitive edge.