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Patent Awarded to Nanoprecise Sci Corp for its Automated Predictive Maintenance Solution

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Business | January 19, 2022 1:20:56 PM IST
Bengaluru (Karnataka) [India], January 19 (ANI/PRNewswire): Nanoprecise is proud to announce that the U.S. Patent and Trademark Office has fully issued a Patent for our AI-based Predictive Maintenance System, under U.S. Patent No. 11,188,065, titled, "System and Method for Fault Diagnosis and Prognosis for Rotating Equipment" on 30th November 2021.

The Patent recognizes our continued development efforts towards bringing a process patent that involves ultra-low-power wireless sensors and cloud-based software that detects even small changes in the machine performance and predicts the remaining useful life of any industrial asset.

RotationLF, analyses complex machine health data automatically using a combination of AI and physics-based models to minimize learning cycles and provide fast return on investment. The incorporation of the CEEMDAN algorithm in to the RotationLF process greatly expands the capabilities of the software by analyzing large amounts of output parameters of the equipment, to identify anomalies and pinpoint faults that has the potential to cause downtime. The AI-based platform takes as little as 5 days to learn and creates a range-bounded baseline for each machine's performance. It identifies faults in real-time to predict failures and also reduces false alarms by up to 90%, compared to competitors.

The MachineDoctor sensor is installed on the rotating equipment and senses different parameters which are then analyzed locally for anomalies before being discarded or sent to the cloud for more intensive review. The cloud server processes the signal through the RotationLF software which uses the most sophisticated CEEMDAN algorithm along with Wavelet Neural Network (WNN) to detect faults and predict the Remaining Useful Life (RUL) of the rotating equipment.

The patent is a significant achievement for Nanoprecise as it represents the high standard of recognition that Predictive Maintenance system being employed by Nanoprecise is unique. Nanoprecise strives to simplify the monitoring of industrial assets involved in the various complex manufacturing processes, with our patented signal processing algorithm, to help manufacturers maximise their uptime.

"We have helped countless asset-intensive organizations to reduce machine downtime and enhance performance & reliability of their assets," says Sunil Vedula, CEO of Nanoprecise Sci Corp. "It is an incredible achievement for us to be granted a patent that officially recognizes our innovation and initiative towards helping manufacturers achieve their maintenance goals."

"To have this unique technique recognised is an amazing accomplishment for us and provides us the opportunity to protect a ground-breaking innovation that has the potential to offer unparalleled benefits to our customers. This is a result of the continued commitment to innovation by our technical team and our relentless pursuit to help drive the industry 4.0 journey for our customers," says Graham Kawulka, Vice President - Business Development, Nanoprecise Sci Corp.

Predictive Maintenance Solution from Nanoprecise

The solution facilitates last mile automation by allowing to be integrated with leading horizontal and vertical technology stacks, via open APIs. It can also be deployed on cloud or on-premise servers. All of these factors allow for a simple plug & play, hassle-free deployment, without worrying about any extra IT infrastructure. Moreover, the automated AI-based analytics platform can be integrated to desktop computers or mobile devices to provide an end-to-end solution that offers peace of mind to all stakeholders.

Nanoprecise provides accurate prognostic and diagnostic solutions that predict the remaining useful life of any asset at any point during its lifetime, thereby empowering users with the right data across several industries.

Visit www.nanoprecise.io to know more

Media Contact:

Tanmay Mhatre

tmhatre@nanoprecisesc.com

CONTACT: +91-9619843789

This story is provided by PRNewswire. ANI will not be responsible in any way for the content of this article. (ANI/PRNewswire)

 
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