Use Machine Learning to alert operators when quality drops
Open in your mobile and put it in your pocket. You will get an alert when quality drops.
Open MobileDisplay in a large screen on the plant floor. Operators can see from far when quality drops.
Open MonitorFind out if a batch will produce a good result or a bad result — without running it.
Open PredictorRe-run the last batch to explore the minimal change to improve batch quality.
Open SimulatorNot sure where to start?
Open the MonitorUsing real-time data of reactor temperature, crystallizer cooling rate, its stirring speed, etc, we show the process progress live, reducing delay.
Using input parameters, we predict whether the batch will be bad (i.e. have course powder). Alerted users can increase crushing time to reduce wastage.
Analysts can re-run any past batch to automatically with parameters needed to fix the batch, reducing re-work and future monitoring cost.
We’ll share questions upfront for us to discuss
Share your process details and input parameters
Share batch & real-time data required for the PoC
We’ll teach you how to build this in a workshop