Welcome & Opening Remarks

8:45am - 9:15am

OEE: Insights, Blind Spots and Better Decisions

OEE is one of the most widely used metrics in manufacturing, but it often oversimplifies complex production realities.  In this session, you will learn how to interpret OEE correctly, recognize its blind spots, and use it alongside other data to drive better, more informed decisions. 

9:15am - 10:00am

Unplanned Downtime & Capacity Loss

Unplanned downtime and small disruptions quietly drain capacity and inflate costs, yet most plants underestimate how much output they’re already losing. In this session, you’ll learn how to make downtime visible, structure it in a way that drives action, and recover hidden capacity—often without investing in new equipment.

10:00am - 10:30am

Interactive Networking Break

10:30am - 11:15am

Process Variation – The Silent Profit Killer

Process variation doesn’t just create scrap, it leads to rework, delays, and warranty risk long before defects are detected. This session shows how real-time monitoring, product and process verification allows teams to catch issues early and take action immediately instead of reacting after the fact.

11:15am - 11:45am

Root Cause & Process Optimization

More data doesn’t automatically lead to better decisions. Without a structured approach, teams stay stuck in firefighting mode.  You’ll learn how to identify the true drivers of process performance, validate improvements with statistical confidence, and turn one-off fixes into repeatable, sustainable solutions.

12:00pm - 1:00pm

Networking Lunch

1:00pm - 2:00pm

(Optional) Designing Better Processes:
Proactive Quality and Process Flow

This session is designed for those who are responsible for designing better.  Learn how organizations model their processes, experiment with unlimited scenarios, and make smarter decisions with simulation software.  For researchers, we will also discuss efficient experimentation.  If you’re optimizing one variable at a time, you’re likely leaving performance on the table. We will explore how design of experiments, predictive modeling, and simulation help you find optimal settings faster, reduce trial-and-error, and build quality into the process from the start.