The Predictive Maintenance AI app offers asset failure prediction with a long-term horizon. It uses a combination of multivariate behavior change algorithms, time and frequency domain analyses, and real-time monitoring with short-term and long-term predictions. This improves the predictability of operations for the assets and enables manufacturers to maximize asset life and productivity.


improvement in production    


reduction in maintenance costs


in yield


improvement in production quality

The approach

Using data from legacy as well as new-age machines, the Predictive Maintenance app creates asset system profiles that identify slow behavior changes or deterioration and predicts failures well in advance. By pairing data with SME inputs, the app delivers improved mean time between failures (MTBF), reduced scrap and improved OEE.

The Neewee Advantage

Failure prediction with a long-term horizon provides early warnings and diagnosis of equipment issues

A multivariate and interdependent approach that considers a wide range of factors

Greater effectiveness and productivity due to system-level modelling instead of asset or component-level modelling

Built-in scalability to easily onboard new assets and systems spread across multiple plants, locations,
and organizations


The Predictive Maintenance AI app can be applied horizontally across all industries to make manufacturing operations more efficient and cost-effective.

Case Studies

Discover how Neewee’s Predictive Maintenance AI app improves equipment uptime and ROI.

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