Design of Experiments and simulation help teams move beyond trial-and-error by testing multiple factors, identifying interactions, and predicting operational performance before committing resources.
Variation can lead to scrap, rework, missed deliveries, warranty risk, and customer dissatisfaction. Real-time monitoring helps teams detect drift earlier, alert operators sooner, and reduce quality losses before they scale.
Small interruptions, unplanned downtime, setup delays, and unclear reason codes can quietly drain productivity. When teams can see downtime clearly and structure it consistently, they can recover capacity without always adding new equipment.
More data alone does not improve performance. Manufacturers need connected systems that make data accessible, timely, accurate, and easy to act on across operations, quality, engineering, and leadership.
OEE helps make downtime, speed loss, and quality loss visible, but it should be used as a diagnostic lens, not just a target. The real value comes from understanding what OEE is helping you see, and what it may be hiding.
Guest Speaker
The Manufacturing Technology Centre: Case Studies of Design of Experiments
The MTC designed experiments in a structured way to maximise the value of test results across aerospace electronics, laser processing, and battery manufacturing projects. By replacing trial-and-error and one-factor-at-a-time testing, teams identified critical process drivers, optimised performance, improved product quality, and accelerated development. Results included up to 130% higher bond strength, 4× greater process performance, and faster, data-driven decisions.
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