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Advanced and automated machine learning-based forecasting that reduces manual effort and improves accuracy. Features include:
Automatic selection of right forecasting level or grain
A wide variety of algorithms that are chosen for each SKU or product category
Error metrics such as MAPE
We use survival curves to predict the failure rates (or maintenance needs) of equipment based on its age, estimated future usage. The survival curves are built using a wide variety of factors and the historical failure data.
Machine learning impact is as good as the decision-makers understand them. We make explaining ML results easier for data scientists as well as decision makers.
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