Optimization of Magnetic Gripper Design for Efficient Robotic Sheet Metal Manipulation: A Comparative Study of Clustering Algorithms

In response to the growing trend of increased product variety in the manufacturing industry, flexible technologies are being employed to enhance production efficiency. This study specifically aims to optimize the design of grippers that manipulate different sheet metal part geometries within a robotic bending cell. The study compares four clustering algorithms to determine the minimum gripper quantity that effectively handles all different production parts. The findings of this study demonstrate that a robust magnetic gripper family, consisting of 4 or 5 grippers, can potentially work with over 927 metal sheet parts while meeting the appropriate dimensions and carrying capacity requirements. Implementing this approach helps minimize engineering changes when introducing new products into the production process.