RICHMOND, VA—The Commonwealth Center for Advanced Manufacturing (CCAM) announced the appointment of two scientists to join the applied research center’s staff and direct the development of new industrial technologies undertaken by CCAM member companies.

“CCAM is delighted to welcome Arvinth Rathinam, manufacturing process engineer, and Daniel Moodie, digital controls engineer–both distinguished engineers whose commitment to manufacturing innovation and collaboration will further the Center’s role in new commercial developments,” said Bob Fagan, Chief Technology Officer. 

Rathinam specializes in CAD/CAM programming, tool and fixture design, machining, statistical quality control, experimental design, sensor deployment and data acquisition, process optimization and automation.  Prior to joining CCAM he was a Research Assistant at Virginia Tech’s Center for Innovation-Based Manufacturing where he developed a multi-sensor test bed for monitoring tool wear in turning processes.  Earlier he was Quality Control Engineer at Bharat Heavy Electricals Ltd. in India.

He holds a Bachelor of Science degree in manufacturing engineering from the College of Engineering, Guindy, Anna University, India, and a Master of Science degree in industrial and systems engineering from Virginia Tech.

Moodie has extensive experience in robotics, calibration of machine vision and structured light systems, and programming user interfaces for vision tools and machine learning.  Prior to joining CCAM he completed a master’s thesis in sensor fused scene reconstruction for mobile robots.  His experience includes working as a software programmer at the Virginia Tech Mechatronics Laboratory and serving as Manufacturing Lead on the university’s Robotics and Mechanisms Laboratory Senior Design Project.  Earlier he developed 3D scanning hardware and software as Senior Software Engineer at VirtualU.  He holds a Bachelor of Science degree in mechanical engineering from Virginia Tech and a Master of Science degree in mechanical engineering with experience in autonomous vehicles and perception, also from Virginia Tech.

For more, visit www.ccam-va.com.