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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.

WEST Session: Join Randy Eickhoff as he breaks down powerful tools that can significantly accelerate depreciation and boost cash flow for manufacturers, facility owners, and real estate investors. This session will cover cost segregation studies, the Section 179D energy efficiency deduction, and Section 179 expensing. With an eye on current IRS positions and pending legislation, Randy will explain how to align tax strategy with capital planning to optimize your bottom line. Expect actionable takeaways tailored for SMEs investing in new buildings, equipment, and improvements.

Speaker at WEST: Tyson Copa, Platform Specialist, IMAGINiT

WEST Session: The modern manufacturing shop floor demands seamless data exchange, real-time visibility, and operational efficiency to stay competitive. IMAGINiT FormsConnected optimizes these workflows by bridging the gap between design, production, and field operations. By digitizing paper-based forms and integrating them directly with Autodesk Fusion Manage and other enterprise systems, FormsConnected ensures accurate data capture, reduces manual errors, and accelerates decision-making. This enhanced connectivity empowers teams to track production status, manage change requests, and streamline quality checks in real time. As a result, manufacturers experience improved productivity, reduced downtime, and greater collaboration across departments, driving measurable gains in efficiency, profitability and overall growth.

Speaker at WEST: Cameron Downs, Chief Executive Officer, Artisan Technologies

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: If you’re in the manufacturing field, then you must be passionate about how things are made. Manufacturing matters, and it’s crucial that leaders step out of their buildings and focus on the business, rather than just working in the business. Most small to mid-sized manufacturers don’t realize there is much power in utilizing peer networks, communities, regions, and states to look from the outside in. We want to leave our businesses in a better condition than when we arrived. We want more youth in manufacturing, we want better data about our manufacturing operations, and we want to understand how to incorporate the newest technology into our operations. Fourteen years in the family’s manufacturing business has allowed me to inform myself and bring solutions to our business and remain competitive. Additionally, amid exploring opportunities, I have discovered the importance of the critical need to bridge the skills gap and the tacit knowledge that is being lost as our skilled workforce retires. The impact that harnessing and leveraging this knowledge will help alleviate the existential crisis that threatens us all.

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Speaker at WEST: Daniel Lyon, Product Manager, Hawk Ridge Systems