Falkonry, Inc., the leading enabler of predictive operations, today announced that its founder and CEO, Dr. Nikunj Mehta, will be speaking at the Semicon West Conference in San Francisco about ways machine learning can help semiconductor companies optimize production uptime and yield. Dr. Mehta will discuss use cases where customers are discovering and recognizing patterns that lead to potential calibration problems or unexpected downtimes in fab operations. They are leveraging machine learning in production to do this and have installed automated warning systems to predict and prevent such issues.
“Just-in-time maintenance of high-precision equipment is a perfect example of how machine learning can help semiconductor companies because a day lost can easily cost hundreds of thousands of dollars in unfilled orders,” said Mehta. “In this case, predictive operations can be leveraged to ensure calibration maintenance occurs exactly when needed, enabling semiconductor manufacturers to significantly reduce, or even eliminate, these unexpected and costly downtime.”
Title of Presentation: Applying “Ready-to-Use” Machine Learning to Improve Production & Yield for Semiconductor Fabrication
Date and Time: Thursday, July 11 at 10:25 am
Location: Room 20, Moscone Center in San Francisco
About Falkonry LRS
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. Depending on the process being monitored, such early warnings may occur hours, days or even weeks in advance. Companies achieve initial results in as little as three weeks, enabling them to save several millions of dollars annually in operating costs and achieve a 5-10 times annual ROI.
Falkonry is the leading enabler of predictive operations for companies looking to achieve significant improvements in the uptime, yield, quality and safety of their operations. Falkonry enables operations teams to discover, explain and predict behaviors that matter, without requiring data scientists. Falkonry’s “pre-packaged” machine learning system, Falkonry LRS, complements a user’s domain expertise to more deeply understand their operations, and can scale across assets, processes and operations. For more information about Falkonry and its products, please visit www.falkonry.com.