Belt Grinding Simulation to Optimize Manual Grinding Process Parameters

Abrasive belt grinding is a manufacturing process used to finish the surface of materials. This process uses abrasive particles of geometrically undefined cutting edges bonded to a flexible cloth. Abrasive belt grinding is often performed manually (manual grinding), and a skilled operator can achieve high quality on complex parts. In manual grinding, the user feels and adjusts the input parameters, such as the grinding force and feed rate, based on the condition of belt wear and machine vibration. How the user controls these parameters in a manual grinding process is poorly understood. One of the downsides of manual grinding is that the depth of cut is complex to maintain compared to an automated grinding process due to an uneven grain penetration in the material with a normal force. Several novel works report research on abrasive belt grinding simulations intended for robot operations, but belt grinding simulations intended for a human-centered approach have not been studied extensively. This research investigates the kinematic belt grinding simulation parameters to improve the manual belt grinding process before a belt grinding process is conducted. A belt-grinding simulation model was created and connected to a graphical user interface (GUI). The belt grinding simulation model app was designed to assist users in predicting grinding process parameters. The input parameters include abrasive belt specification (grit size and belt dimension), feed rate, and cutting speed. The simulation outputs the average surface roughness, grinding time, and depth of cut, informing the user of the process’s effectiveness. First, the user inputs the input process parameters. Then, the simulation generates the belt topography, approximating the grits as spheres, and generates a workpiece with an estimated initial surface quality. Once the belt topography is generated, the grinding process is simulated with a suggested feed rate, cutting speed, and force. The result will be compared to a grinding process to validate the simulation predictions. The novelty of the shown work is that it is a simulation tool for manual operations that allows user input and interaction with the simulation before the grinding operation is conducted. Future sensor integration and force calculations will allow better manual operations and worker training guidance.