On-Demand Webinar
Long gone are the days when designing a motor control application was focused on just getting the motor turning. Engineers are now challenged to add additional features on increasingly complex and multifunctional motor control equipment, while reducing time-to-market, minimizing end-product and maintenance costs, and ensuring safe and secure operation of their designs.
One such feature, predictive maintenance based on AI, has become a common requirement for IoT motor control designs because of its ability to enable preemptive corrective actions, reduce maintenance costs, increase asset life, and ensure safety compliance.
In this webinar, we will explore:
- The RA6T1 single-chip MCU optimized for motor control to help lower overall BOM cost
- A full RA6T1 motor solution to easily evaluate and debug motor control applications and reduce development time and effort
- A predictive maintenance solution with AI using the Google TensorFlow™ Lite for Microcontrollers framework to reduce maintenance costs
Presented by:
Takeo Mimura
Senior Staff Engineer
Renesas Electronics
Takeo Mimura joined Renesas in 2007 and has since been in charge of product marketing for SuperH / RX MCUs. Currently, he oversees the RA6T1 MCU Group, the latest members of the RA MCU Family that are designed to make motor control easy.