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Transform your manufacturing operations with secure, intelligent IIoT solutions that turn machine data into measurable results.

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A CPS Protection Platform that enables premium service, and control over industrial assets. Drive new capabilities with no-code applications that deliver immediate value.

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Guides AI / Data Science

Predictive Maintenance

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Implement practical predictive maintenance based on proven machine learning techniques.

Our technical paper details real-world experiences in forecasting machine downtime using machine learning classification algorithms trained on historical machine data from industrial printing equipment.

Our approach to predictive maintenance offers:

Data-driven failure prediction
Reduced unplanned downtime
Practical implementation strategies
Minimal false-positive alerts

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In this guide, you will discover:

Machine learning classification methods

A detailed explanation of the algorithms and approaches used to transform operational data into actionable predictions for maintenance planning.

Data analysis challenges and solutions

Practical strategies for overcoming common obstacles in industrial data collection, including missing values, measurement errors, and separating operator impact from machine behavior.

Implementation success metrics

How to evaluate and measure the real-world impact of predictive maintenance solutions, balancing true positives, false positives, and the practical economics of maintenance decisions.