Monitor manufacturing equipment in real time and track its full lifecycle to predict and prevent equipment failure, reduce downtime, and optimize processes. The Neal Analytics predictive maintenance solution combines advanced data analysis, artificial intelligence algorithms, and IoT built on Microsoft Azure with Intel technology to help you control costs and improve product quality.
Reduce downtime and costs
Lower operating and maintenance costs and reduce financial risk.
Prioritize line-manager and operator tasks based on insights.
Improve product quality
Identify and correct process anomalies that lead to defects.
Glass company predicts breakdowns with 85% accuracy, two days in advance
An international glass manufacturer was experiencing equipment failures that led to unexpected costs and low production availability. Using the Neal Analytics Predictive Maintenance solution, which includes Microsoft Azure Machine Learning, the company can identify variables and anomalies that influence equipment failure. This solution enables the company to predict breakdowns two days in advance with 85% accuracy and take appropriate action, resulting in lower maintenance costs and less unplanned downtime.
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