HARMAN and Intel Partner On Real-Time Predictive Analytics, an IIoT Solution for Industrial Rotating Equipment

Author photo: Alex Chatha
ByAlex Chatha
Category:
Acquisition or Partnership

HARMAN, a premier connected technologies company for the automotive, consumer, and enterprise markets, and Intel Corporation announced HARMAN Quick Predict, an end-to-end industrial Internet of Things (IoT) solution that provides early detection of problems with rotating equipment in industrial settings.  HARMAN's leading engineering services team developed Quick Predict based on a vibration analytical algorithm developed by Intel.

Unlike other systems, HARMAN Quick Predict generates predictions based on real-time information instead of historical data collected over time.  Using advanced machine learning algorithms, the solution enables prediction of potential failure based on capture and analysis of abnormal vibration patterns at the gateway, which are detected and flagged.

The collaboration uses a vibration analytical algorithm developed by Intel and HARMAN Connected Services' Mobile and Communications Services' team to deliver an operational product.  With HARMAN Quick Predict, enterprises are able to increase equipment uptime, decrease spare parts costs, and optimize the use of their workforce by reducing the number of emergency repairs.  The solution collects the high-resolution vibration data needed to detect problems early and provides learning analytics that help map abnormal vibration and rotation speed patterns to associated failure mechanisms.

Rotating equipment maintenance is expensive and resource intensive.  Even with full spare parts and machinery in place, a pump failure on a line can cause costly production delays leading to emergency work orders and hurried scheduling of maintenance crews.  Spot manual vibration readings collected under preventative maintenance programs on a weekly or monthly basis by technicians simply do not provide the data needed to identify all problems early enough to allow for planned repair.

Keywords: Industrial IoT, Predictive Maintenance, Rotating Equipment, Advanced Machine Learning, Abnormal Vibration, Vibration Analytical Algorithm, ARC Advisory Group.

 

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