How Operational Machine Learning Transforms Industrial Operations

A.I. is rapidly shifting from an emerging tool manufacturers should learn about to one they should deploy. This infographic should help you figure out where you fall.

Artificial intelligence is the umbrella term for the legion of algorithms and chatbots and programs pervading the digital world. Operational machine learning may be the branch that makes AI relevant in your real life. Without the aid of data scientists, the combination of machine learning and predictive analytics allows operations teams, including Toyota and Honda's, to create a great deal of business value.

“Operational machine learning allows manufacturing and process engineers to leverage their existing, underutilized operations data and provide insights that significantly improve uptime, quality and performance," Nikunj Mehta, Founder and CEO of Falkonry.

The company paltform, Falkonry LRS, offers supervised and semi-supervised machine learning to teams right now to discover hidden patterns, provide early warnings and analyze existing multivariate time-series data from your operations.

“Every customer we engage with has time series data just waiting to be leveraged by Falkonry LRS, and customers typically gain actionable insights from this data in less than three weeks," Mehta says. "This is significant because the operational improvements can result in savings of several millions dollars annually for just one customer.”

To see if you can scoop up some of these savings, you should probably learn a bit more about what operational machine learning is. Falkonry made the below infographic to give you a quick overview.



TAGS: Automation
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