Surface Roughness Prediction in Grinding: a Probabilistic Approach
Surface quality of machined components is one of the most important criteria for the assessment of grinding processes. The importance of surface finish of a product depends upon its functional requirements. Since surface finish is governed by many factors, its experimental determination is laborious...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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EDP Sciences
2016-01-01
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| Series: | MATEC Web of Conferences |
| Online Access: | http://dx.doi.org/10.1051/matecconf/20168201019 |
| _version_ | 1818368840776548352 |
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| author | Saxena Krishna Kumar Agarwal Sanjay Das Raj |
| author_facet | Saxena Krishna Kumar Agarwal Sanjay Das Raj |
| author_sort | Saxena Krishna Kumar |
| collection | DOAJ |
| description | Surface quality of machined components is one of the most important criteria for the assessment of grinding processes. The importance of surface finish of a product depends upon its functional requirements. Since surface finish is governed by many factors, its experimental determination is laborious and time consuming. So the establishment of a model for the reliable prediction of surface roughness is still a key problem for grinding. In this study, a new analytical surface roughness model is developed on the basis of the stochastic nature of grinding processes. The model is governed mainly by the random geometry and the random distribution of cutting edges on the wheel surface having random grain protrusion heights. A simple relationship between the surface roughness and the chip thickness was obtained, which was validated by the experimental results using AISI 4340 steel in surface grinding. |
| first_indexed | 2024-12-13T23:14:21Z |
| format | Article |
| id | doaj.art-a30a6140347048959b75054a461e3ed1 |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-12-13T23:14:21Z |
| publishDate | 2016-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-a30a6140347048959b75054a461e3ed12022-12-21T23:27:59ZengEDP SciencesMATEC Web of Conferences2261-236X2016-01-01820101910.1051/matecconf/20168201019matecconf_d2me2016_01019Surface Roughness Prediction in Grinding: a Probabilistic ApproachSaxena Krishna Kumar0Agarwal Sanjay1Das Raj2Department of Mechanical Engineering, Centre for Advanced Composite Materials, University of AucklandDepartment of Mechanical Engineering, B.I.E.T.Department of Mechanical Engineering, Centre for Advanced Composite Materials, University of AucklandSurface quality of machined components is one of the most important criteria for the assessment of grinding processes. The importance of surface finish of a product depends upon its functional requirements. Since surface finish is governed by many factors, its experimental determination is laborious and time consuming. So the establishment of a model for the reliable prediction of surface roughness is still a key problem for grinding. In this study, a new analytical surface roughness model is developed on the basis of the stochastic nature of grinding processes. The model is governed mainly by the random geometry and the random distribution of cutting edges on the wheel surface having random grain protrusion heights. A simple relationship between the surface roughness and the chip thickness was obtained, which was validated by the experimental results using AISI 4340 steel in surface grinding.http://dx.doi.org/10.1051/matecconf/20168201019 |
| spellingShingle | Saxena Krishna Kumar Agarwal Sanjay Das Raj Surface Roughness Prediction in Grinding: a Probabilistic Approach MATEC Web of Conferences |
| title | Surface Roughness Prediction in Grinding: a Probabilistic Approach |
| title_full | Surface Roughness Prediction in Grinding: a Probabilistic Approach |
| title_fullStr | Surface Roughness Prediction in Grinding: a Probabilistic Approach |
| title_full_unstemmed | Surface Roughness Prediction in Grinding: a Probabilistic Approach |
| title_short | Surface Roughness Prediction in Grinding: a Probabilistic Approach |
| title_sort | surface roughness prediction in grinding a probabilistic approach |
| url | http://dx.doi.org/10.1051/matecconf/20168201019 |
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