A two-step machining and active learning approach for right-first-time robotic countersinking through in-process error compensation and prediction of depth of cuts

Exploring foci of: Robotics and Computer-Integrated Manufacturing • Vol 77 A two-step machining and active learning approach for right-first-time robotic countersinking through in-process error compensation and prediction of depth of cuts March 2022 • Mateo Leco, Thomas E. McLeay, Visakan Kadirkamanathan Robotic machining processes are characterised by errors arising from the limitations of the industrial robots. These robot-related errors can compromise the overall manufacturing process performance, resulting in final products with dimensions different from the nominal specifications. To avoid accumulation of errors through several manufacturing stages, a quality inspection step is usually performed after the cutting operation. This work presents an innovative two-step manufacturing method for achieving right-fir… Open Article Page

Machining Process (Computing) Computer Science Robot Artificial Intelligence Engineering Mechanical Engineering Open Article