4.6 Article

The influence of wear volume on surface quality in grinding process based on wear prediction model

Journal

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
Volume 121, Issue 9-10, Pages 5793-5809

Publisher

SPRINGER LONDON LTD
DOI: 10.1007/s00170-022-09575-5

Keywords

Grinding; Surface quality; Wear model; Wear volume; Grinding temperature; Surface morphology

Funding

  1. National Natural Science Foundation of China [52175113, 51905406]
  2. Key Laboratory Research Program of Education Department of Shaanxi Province [18JS044]
  3. International Science and Technology Cooperation and Exchange Program of Shaanxi Province

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This study proposes a new physical model for wear prediction in the grinding process, based on the finite element method and numerical simulation technology. Experimental results validate the accuracy of the model. The findings are important for wear prediction and surface quality control in the grinding process.
During the grinding process, the workpiece is not only cut by abrasive grains but adhesive wear also occurs due to high temperature and heavy load, reducing the surface quality of the workpiece. In this paper, a wear test method considering speed, force, wear coefficient, temperature and hardness was proposed. A new physical model of wear prediction was established based on the finite element method and numerical simulation technology. The wear test was carried out on a grinding machine. Comprehensive research on the relationship between the force, temperature, surface morphology and wear volume of the grinding process was studied. The relationship between workpiece speed, grinding depth, cooling lubrication conditions and wear volume of the grinding process was studied. The results show that the wear model can achieve numerical prediction and trend prediction of grinding temperature, surface profile and wear volume, with relative errors between the theoretical and actual values of wear and grinding temperature of 9.84% and 2.07%, respectively. This study provides support for wear prediction and surface quality control of the grinding process from the perspective of temperature and micro material removal.

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