CN 41-1243/TG ISSN 1006-852X
Volume 45 Issue 4
Aug.  2025
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Article Contents
PENG Fei, ZHANG Yanbin, ZHANG Rukang, CUI Xin, XU Peiming, DONG Lan, ZHANG Xiaotian, SONG Xuelei, LI Changhe. Research progress on abrasive geometry modeling and application[J]. Diamond & Abrasives Engineering, 2025, 45(4): 427-447. doi: 10.13394/j.cnki.jgszz.2024.0165
Citation: PENG Fei, ZHANG Yanbin, ZHANG Rukang, CUI Xin, XU Peiming, DONG Lan, ZHANG Xiaotian, SONG Xuelei, LI Changhe. Research progress on abrasive geometry modeling and application[J]. Diamond & Abrasives Engineering, 2025, 45(4): 427-447. doi: 10.13394/j.cnki.jgszz.2024.0165

Research progress on abrasive geometry modeling and application

doi: 10.13394/j.cnki.jgszz.2024.0165
More Information
  • Received Date: 2024-10-16
  • Accepted Date: 2025-02-10
  • Rev Recd Date: 2025-01-07
  •   Significance  Abrasives are recognized as indispensable in precision machining, and their role in processing critical components has been firmly established. Geometric modeling of abrasives is regarded as essential for quantitative characterization of material removal, as it exerts substantial influence on the prediction of machining forces, thermal effects, and surface roughness. However, consistent guidance on modeling methodologies remains lacking, and controllable fabrication of abrasive geometries has persisted as a critical challenge requiring further investigation.  Progress  Abrasives are regarded as fundamental to precision machining and are considered essential for modeling material removal. In prior studies, abrasive geometries have typically been simplified as regular forms, such as spheres, cones, frustums, and truncated polyhedra. However, actual abrasives predominantly exhibit irregular polyhedral shapes, and their interaction mechanisms are not fully represented by these simplified models. To address this limitation, a random plane-cutting method has been developed on the basis of prior studies. In this method, realistic abrasive geometries are generated by intersecting regular shapes with randomly oriented planes, enabling quantitative analysis of material removal and surface roughness. Based on abrasive retention, abrasive machining is commonly categorized as fixed or free abrasive processing. In free abrasive machining, material is removed from the workpiece surface by free abrasives, primarily through lapping and polishing. By contrast, fixed abrasive machining is performed by fixing abrasives within a bond matrix. Although substantial differences exist between these methods in machining mechanisms, abrasive utilization, and fluid requirements, the accuracy of abrasive shape modeling has been shown to exert a significant influence on grinding force, heat generation, and surface roughness. Abrasive preparation is defined as a shape-forming process in which raw abrasives are processed into defined geometries, sizes, and properties to satisfy various industrial requirements. Grinding wheel dressing is recognized as a critical operation to maintain the profile, dimensional accuracy, and surface topography of the grinding wheel, and comprises two primary steps: truing and sharpening. Among these steps, micron-scale truing is conducted at the abrasive level, representing abrasive shaping. At present, abrasive shaping methods based on laser processing and thermochemical graphitization removal are regarded as major research focuses.  Conclusions and Prospects  Currently, abrasive geometries are primarily modelled as spheres, cones, frustums, and polyhedral. Abrasive modeling has been extensively applied in precision finishing processes utilizing both free and fixed abrasives. A range of abrasive manufacturing and shaping techniques has been investigated in recent studies, encompassing micro-mould replication, transfer-assisted screen printing, laser cutting, laser micro-structuring, and dressing methods based on the combined action of discharge heat and alternating cutting forces. A new perspective has been introduced through artificial intelligence-based abrasive modeling, and the development of intelligent systems integrating domain knowledge and data should be prioritized in future research. Furthermore, pixel-level recognition of multiple target abrasives in imaging data can be achieved through artificial intelligence algorithms. The integration of artificial intelligence with laser sintering and 3D printing is expected to enable precise fabrication of abrasives with controllable geometries. The implementation of online monitoring techniques facilitates accurate assessment of abrasive wear during machining, thereby providing data to support tool design and optimization.

     

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