Efficient inspection planning for coordinate measuring machines

The coordinate measuring machine (CMM) has been recognized as a powerful tool for dimensional and geometric tolerance inspection in the manufacturing industry. The power of the CMM depends heavily on an efficient inspection plan that measures a part in minimal time. This paper proposes CMM inspection planning that can minimize the number of part setups and probe orientations and the inspection feature sequence. In our planning, a greedy heuristic method is adopted to obtain the minimal number of part setups and probe changes. Meanwhile, a continuous Hopfield neural network is developed to solve the inspection feature-sequencing problem. The proposed method was successfully implemented and tested using a machine spindle cover part. The results show that the proposed method can achieve excellent performance compared to the other methods.