Knowledge Sharing enabled Multi-Robot Collaboration for Preventive Maintenance in Mixed Model Assembly

Intelligent equipment and flexible production lines are at the cores of smart manufacturing. Meanwhile, Internet of Things and Artificial Intelligence have provided new solutions for the intelligent equipment management and maintenance in mixed model assembly (MMA). This article focuses on knowledge-driven techniques, and it proposes a knowledge sharing-enabled multirobot collaboration (KS-enabled MRC) strategy for preventive maintenance of robots in MMA. First, a formal semantic environment for MMA is constructed by way of ontology-enabled semantic modeling. Then,task-related action primitives and ontology-based robot skill bases are established according to robot capability and task environment. Finally, the Wu-Palmer similarity metric and first-order logic are leveraged to match and reason new tasks according to the semantic rules, and a knowledge sharing and update mechanism are developed for this application. Experimental results demonstrate that the proposed KS-enabled MRC can reduce unscheduled downtime and assist in achieving a load balance for robots in MMA. The studied MRC can potentially avoid severe equipment degradation, thus acting as a preventive maintenance paradigm of complex equipment. Furthermore, it is applicable across different platforms and exhibits high deployment efficiency without intense programming requirements.