VIMANA’s Founder part of NIST workshop on Smart Manufacturing Systems, Performance Assessment – Monitoring and Measurement Panel

Berkeley, CA – VIMANA announced that company founder and Chief Strategy Officer, Will Sobel participated in the Performance Assessment – Monitoring and Measurement Panel, for a workshop conducted by the National Institute of Standards and Technology (NIST). The workshop was conducted on Measurement Science for Prognostics and Health Management for Smart Manufacturing Systems, where Will Sobel spoke about how VIMANA’s predictive analytics can be applied for prognostics and health management.

Will Sobel, Founder and Chief Strategy Officer of VIMANA, stated, “Most manufacturing processes are run sub-optimally from a tool and performance perspective. Now that improved sensors and technologies are becoming available, real-time data analytics, downtime and process improvement, and prognostics that go beyond machine health are possible. Presently, there are no common standards for the level(s) in which diagnostic and prognostic activities need to occur on onboard equipment vs. in the cloud. Flex computing at VIMANA (commonly referred to as fog computing), takes an integrated approach by performing big data analytics in the cloud, in addition to shop floor processing, to find optimal process parameters for use in production.”

 

NIST recently released the full report from the workshop, that lays out a roadmap for building Prognostics and Health Management systems, and it can be found at http://www.nist.gov/el/isd/phm4sms-workshop.cfm.

Dr. Athulan Vijayaraghavan, Chief Technology Officer and co-founder of VIMANA, said, “The advanced pattern matching capabilities of VIMANA make it very suitable for analyzing the health of individual manufacturing equipment, or the entire manufacturing system itself. The health of the equipment (or the system) can be considered as purely its maintenance state, or even as its overall operational state; VIMANA makes it possible to derive these states, and then drive decisions to improve the equipment/system performance.”

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