Impacts of heterogeneous autonomous mobile robots (AMRs) on smart manufacturing

Robotic-cell manufacturing with robotic arms for material-handling are known to be efficient in manufacturing. However, constructing robotic arms in each robotic cell is costly and inefficient. Nowadays, with the advancement of autonomous mobile technology, autonomous mobile robots (AMRs) can be equipped with different robotic arms, and therefore the robotic arms can be shared by the robotic cells. However, this dramatically increases the optimization complexity due to the new decisions induced by the (robotic) arms-to-cells assignment/scheduling problem over the traditional robotic cells scheduling problems. In addition to the heterogeneous AMRs and the potential deadlock problem involving in the loading and unloading of workpieces on feeders, the problem becomes even more complicated. Thus, to tackle the problem, this paper presents a tailored matheuristic method with an innovative deadlock-free strategy. Numerical experiments are conducted based on both real and semi-real industrial data. The results demonstrate that the proposed tailored matheuristic method outperforms other existing meta-heuristics about 10–20 %. Moreover, we found that the performance of the system is sensitive to the traveling time and processing time, and thus the performance of using shared AMRs is even better in some situations.