This presentation will explore how AI is transforming digital fabrication, from design optimization to real-time quality control. Attendees will gain insights into practical AI implementation strategies, data-driven decision-making, and best practices for enhancing manufacturing processes. Real-world case studies will illustrate how AI can improve efficiency, reduce costs, and drive innovation. Whether you’re a designer, engineer, or business leader, this session will provide actionable steps to integrate AI effectively within your workflows.

Achieving production excellence doesn’t require massive overhauls — it’s about focusing on the small, high-impact actions that drive continuous improvement. This session introduces the concept of High Payoff Activities (HPAs) in manufacturing, covering five key areas: Safety, Quality, On-Time Delivery, Cost Reduction, and Continuous Improvement.

Attendees will learn how prioritizing these activities — in the right order — helps improve performance, reduce waste, and strengthen customer satisfaction. Join us to explore practical ways to build a culture of improvement and move your production team closer to excellence, one step at a time.

Counterfeit Parts is a highly lucrative market, and the criminals continue to improve their counterfeit parts and paperwork to pawn off to unsuspecting buyers. Keeping abreast of the methods necessary to prevent inadvertent purchasing of counterfeit parts requires a high level of vigilance and discipline. It requires collaboration between your customer, your buyers, the independent brokers, independent testing laboratories and your receiving inspection department.

All manufacturers need to understand their overall line’s capacity, and each process’s capacity, to plan and keep up with growing customer product demand and changing product mix.  In addition to keeping up with product demand, it is important to understand future equipment needs for the purpose of forecasting required space, capital, and labor.

Many small to medium-sized companies do not have the enterprise resource planning tools, or in-house expertise, to readily develop these production capacity forecasts.  The methodology discussed in this presentation provides answers to the above business needs by considering the following attributes:

• Products manufactured
• Expected product demand for the foreseeable future
• Process flow for each product
• Equipment used for each process
• Equipment used for each material movement
• Processing rate at each process step
• Process yield (scrap rate) at each process step
• Equipment reliability (unplanned downtime) and preventive maintenance time
• Labor required at each process step and material movement

Applying the above attributes, using a common spreadsheet, future needs for equipment, space, capital, and labor are forecasted.  Once equipment needs over time are understood, it is also possible to identify a floorplan designed for minimally disruptive growth, and opportunities for automation, more sophisticated equipment, and utility usage reduction.