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FINNISH ZYFRA RANKED TOP 10 INDUSTRIAL SOLUTIONS AT IOTSWC

10/19/2018

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Post By Simon Montford on Oct 19, 2018
ZYFRA became one of 10 companies selected as a participant of a TESTBEDS section of the IoT Solutions World Congress held in Barcelona on the 16th–18th of October. Digital Advisor is a recommendations system for industrial enterprises that presents to the operator a specific guide to action to achieve the target parameters (energy efficiency, quality, productivity). “We are proud of being featured among 10 best AI solutions in real production sector projects and be presented in a TESTBEDS section”, said Dmitry Lukovkin, AI Business Director of ZYFRA.
Finland-based company ZYFRA, specialises in Artificial Intelligence (AI) and Industrial Internet of Things (IIoT) based solutions for industries that include metallurgy, oil and gas and mining.

The company applies cutting edge data science combined with industrial expertise to provide end-to-end solutions help machinery to optimise production speed, quality, and cost.

During the conference, ZYFRA introduced its real-time machine data collection system MDCplus can be used to track jobs, operations, work centres, scrap, costs, downtime, and people, and demonstrated its industrial AI solution. At its show-bench the company offered exhibition visitors a simulated steelmaking "man versus machine" challenge. Their solution can either predict quality and product properties, or recommend process settings and material usage. By learning from historic operational data, the company's industrial AI solution can significantly increase productivity. 

During IOTSWC, Dmitry Lukovkin was invited to join the panel “Artificial intelligence for oil and gas industry processes control and optimisation. AI perspective and lessons learned”.

ZYFRA, founded in November 2017, currently operates in Bulgaria, Finland and India. The company connected over 7,000 CNC machines. ZYFRA technologies allow customers to drastically boost machinery utilisation efficiency and improve the accuracy of product quality prediction. 

Further information can be found on the company's website: http://www.zyfra.com/en/#technologies
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