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Applications for predictive analytics are endless, but a possible first step: engineers can use analytics to monitor manufacturing sensors for reliability and operational performance.
Bad sensor data can mean lost product, downtime, compliance issues, and safety risks as well as a dirty data foundation for digital transformation and continuous improvement programs. Industrial organizations need to have good data that can be leveraged for operations, ad hoc analysis, and enterprise analytics.
Over time, manufacturing sensors tend to deviate, impacting processes and operations. But, it’s time consuming – and impossible for most organizations – to manually determine if and why sensors are working or failing ahead of increasing risk.
Engineers can employ a predictive analytics software such as Proficy Sensor Health to continuously monitor and analyze sensor data. Users can target anomalies and minimize their potential impact. The analytics app provides an easy way to automate the detection of bad sensors, where data is deviating from normal conditions.
When an anomaly is detected, the software can generate alarms to speed repairs, replacements, and recalibrations.
By using predictive analytics software to monitor sensor health, engineers can:
Explore how Proficy CSense helps engineers analyze, monitor, predict, simulate, and optimize setpoints in real time. For a limited time, we are offering a free trial so you can experience the power of Industrial AI in your operations.
Register today to download your free Proficy CSense software!
Automatically generate alerts to speed response
Bad sensor data can mean lost product, downtime, compliance issues, and safety risks as well as a dirty data foundation for your digital transformation and continuous improvement programs.
As an embedded smart app, Proficy Sensor Health continuously monitors and analyzes sensor data, learning patterns and applying intelligence. You can target anomalies and quickly minimize their potential impact.