Bayesian modeling of the risk of non‐repeatability for the networked robotic system

This study addresses one of the most important performance criteria, namely the robot’s repeatability, from the e‐quality for manufacture (EQM) point of view within the framework of networked robotic system. Real‐time monitoring and control of remotely located robots allow the operators to continuously assess the risk of robot’s non‐repeatability. The elaborated methodology of predictive modeling on the risk of robot’s non‐repeatability consists of three stages: (1) regression analysis on the association between the disturbing factors and the key performance variables that influence the robot repeatability; (2) probabilistic assessment on the admissible deviations of key performance variables that simulate the robot operations as probabilities of job service without failures in the queueing system; and (3) Bayesian assessment on the risk of non‐repeatability for the robot operations. The proposed methodology is expected to reduce the risk of robot’s non‐repeatability, which is better suited for today’s networked, distributed production environment, where quality standards are stringent and customer expectations are high.