Generating complex assembly sequences from 3D CAD models considering insertion relations

To reduce human intervention in the process of manually teaching assembly sequences to industrial robots, we developed an automated sequence planning method using only a 3D CAD model. In the proposed method, first, to find an assembly sequence for many parts, a genetic algorithm generates the initial chromosome based on interference, rather than merely generating a randomized initial chromosome. Second, to generate an assembly sequence satisfying the preferred insertion condition (e.g. male–female parts), we calculate an insertion matrix indicating the insertion relations between the parts. In this paper, the preferred insertion condition is defined as requiring a part with holes to be prepared first, and then other parts are inserted into the holes. In our experiments on assembly sequence generation both with and without the proposed methods, the proposed method was able to generate an assembly sequence for a product composed of 32 parts. The proposed method generated a feasible sequence every time (30 successes in 30 trials) and a preferable sequence, such as fixing by a screw after assembling the fixed part. These results demonstrate the usefulness of the proposed chromosome initialization method and the use of insertion matrices.