Agents find the gap between how your processes run and how they could. Better parameters, faster transitions, more output — surfaced as specific recommendations your team can act on.
“…we could immediately find opportunities for optimizing the cycle time. In some of the cases, we could see that in certain products, we could optimize up to twelve minutes of reduction in the cycle time, which for a three hour batch is a pretty big outcome.”
Agents analyze how each process actually runs — decomposing changeovers phase by phase, comparing setpoints across lines running the same product, and surfacing where one line consistently outperforms another. The gap between best and average is always there; agents find it.
By correlating historical process parameters with output quality and yield, agents identify the setpoints that produce the best results for each product — not just the fastest changeover, but the optimal way to run. The result is a playbook for every product-to-process combination.
When a process starts or a changeover begins, the agent surfaces the optimal parameters for that specific product — flagging deviations in real time and keeping the run on the best-known path.