An adaptive-group-based differential evolution algorithm for inspecting machined workpiece path planning

In the precision manufacturing process, accuracy and precision are crucial when designing a workpiece inspection system. An efficient system minimizes inefficiencies caused by workpieces failing to meet customer needs and delays caused by slow workpiece inspection. In this study, a workpiece inspection system for measuring path planning is proposed that uses the given coordinate of inspection points discerned from 3D images. Then, an adaptive-group-based differential evolution (AGDE) algorithm is used to optimize the measuring path. The AGDE algorithm incorporates the grouping concept into conventional differential evolution, and this improves local search ability through referencing the direction of the best solution in each group. By using the proposed method, the shortest non-colliding measuring path is obtained. Moreover, the proposed workpiece inspection system shortens the workpiece inspection time and achieves faster performance than manual measuring path planning under multiple workpiece inspection points.