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Falkonry to speak ITAP 2019 event

Source:Ringier Metalworking Release Date:2019-10-21 278
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  Falkonry, Inc., an enabler of predictive operations for Global 2000 companies, announced its participation at Industrial Transformation ASIA-PACIFIC (ITAP) 2019, the HANNOVER MESSE trade event for Industry 4.0 in Asia Pacific.  

Falkonry will be speaking on a panel to discuss how companies can achieve digital innovation at scale, highlighting how the Falkonry LRS machine learning system and its edge analyzer capability has been successfully used to detect, predict and explain conditions preceding equipment failures, resulting in reduced unexpected downtimes and savings of hundreds and millions of dollars annually. Falkonry will also be on site in the Siemens booth #1K12, showcasing the benefits of Falkonry LRS and a demonstration of the edge analyzer running on a Siemens edge device.

Falkonry Speaker: Sanket Amberkar, SVP Marketing and Partnerships
Date/time: October 23, 2019 at 12:30 pm
Title of Presentation: Digital Innovation at Scale: from Data Chaos to Business Impact
Location: Siemens stage area in Hall 1 of the Singapore Expo, Singapore

About Falkonry LRS and Edge Analyzer

Unlike other analytics technologies, Falkonry LRS can be quickly and easily deployed by manufacturing engineers or process engineers - without requiring data scientists. The system applies automated feature learning to multivariate time series data that is generated by the equipment and production systems in most discrete manufacturing and industrial process operations. It is able to discover hidden patterns in the data that cannot be observed by humans or traditional analytics. These patterns in turn provide insight on the operating state and identify conditions that precede undesired events and are used to provide an early warning. The Edge Analyzer, which is available as part of Falkonry LRS, is a portable self-contained engine that enables customers to deploy predictive analysis on edge devices for low latency applications in disconnected environments or close to data sources.

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