Material kitting in selective assembly: a manual order picking system based on augmented reality

In the process of selective assembly for precision and complex mechanical products, it is necessary to perform the selective material kitting one by one and conduct check repeatedly according to the optimal matching result to ensure quality. The traditional manual picking and checking method by Bill of Material is inefficient and laborious. Currently, there is still no consensus reached on how to better transmit information and implement the material kitting in the course of selective assembly. In this paper, we pioneer in testing the performance between mainstream methods (Pick-by-Voice, Pick-by-Light, Pick-by-AR) and traditional methods (Pick-by-Paper) in terms of task time, errors, workload, and information perception for the selective material kitting. We developed an AR (augmented reality) on the level of material individual information level and verified its applicability. Meanwhile, we enhanced the effect of material individual information expression from different visual perspectives. We found that Pick-by-AR can outperform others in terms of selective assembly, which means expanding the dimension of information expression and enhancing users’ perception of information can help users quickly and accurately select parts with the same appearance but different quality characteristics fast and accurately, thus providing a viable option for material kitting in the selective assembly process.