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Quality prediction at scale

We combine accuracy with robustness

Quality prediction

Why it’s useful

Production processes are increasingly complex and integrated which means that defects are at the same time more likely to happen and cost more when they happen.

In addition, existing defect anticipation solutions are unadapted and cumbersome, so more reliable solutions able to model complex processes are needed.

Production processes are increasingly complex and integrated which means that defects are at the same time more likely to happen and cost more when they happen.

In addition, existing defect anticipation solutions are unadapted and cumbersome, so more reliable solutions able to model complex processes are needed.

Robustness

Why it’s important

Production processes are not only complex but dynamic.
New products, new machines or even maintenance schedules on the same machine can generate different data which impacts the performance of predictive models

Those models therefore need to be highly robust and maintain a stable predictive performance over time

Production processes are not only complex but dynamic

New products, new machines or even maintenance schedules on the same machine can generate different data which impacts the performance of predictive models

Those models therefore need to be highly robust and maintain a stable predictive performance over time

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