Surface Roughness Prediction in Grinding: a Probabilistic Approach

Saxena, Krishna Kumar; Agarwal, Sanjay; Das, Raj

doi:10.1051/matecconf/20168201019

Cited by 7 publications

(4 citation statements)

References 12 publications

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“…A number of models have been constructed by several authors with different assumptions summarized in Table 1. T he cross-section of the scratches of each abrasive brain left on the surface workpiece is semi-circular shape (4) 5 = 0.92 * ℎ Krishna Kumar Saxena et al [7] T he cross-section of the scratches of each abrasive brain left on the surface workpiece is semi-circular shape (5) In the above formulas, hm is the undeform chip thickness. The value of hm depends on many parameters s uch as cutting parameters, grinding wheel type, grain size, etc, and is defined as follows [8]:…”

Section: Some Models Predict the Surface Roughness Of Workpiece When Grindingmentioning

confidence: 99%

Prediction of Surface Roughness When Surface Grinding C45 Steel Using CBN Grinding Wheel

Thien¹,

Trung²,

Ky³

et al. 2020

ujme

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This paper presents a study of the roughness prediction of the workpiece when using CBN (Cubic Boron Nitride) grinding wheel to process C45 steel on a surface grinder. On the basis of inheriting the previously published studies on modeling surface roughness of workpiece when grinding, this study was conducted to develop one of these models and build a new model of surface roughness that consider many factors affecting surface roughness. Cutting parameters, parameters of grinding wheel, characteristics of materials, characteristics of contact of grinding wheel with workpiece have been included in the roughness model of the surface roughness of workpiece. This new surface roughness model was used to predict surface roughness of workpiece when grinding C45 steel with CBN grinding wheel. The results showed that the surface roughness value when predicting was very suitable for the experiment and the average deviation between the predicted results and the experimental results was only about 9.84%. The surface roughness model proposed in this study also confirms that the roughness can be predicted more accurately than the previous surface roughness models. And then, the development direction for further research is also mentioned in this paper.

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Section: Some Models Predict the Surface Roughness Of Workpiece When Grindingmentioning

confidence: 99%

Prediction of Surface Roughness When Surface Grinding C45 Steel Using CBN Grinding Wheel

Thien¹,

Trung²,

Ky³

et al. 2020

ujme

View full text Add to dashboard Cite

show abstract

“…(10) ( ) = 0.92 (ℎ), [15] Hypothesis was that shapes of scratches of the grinding particles leaving on the workpiece surface was the curved arc of a quarter circle. (11) The above cited surface roughness models showed that depending on the different hypotheses about the shapes of the scratches of the grinding grains left on the workpiece surface.…”

Section: Modelsmentioning

confidence: 99%

Development of the Surface Roughness Model in the Grinding Processes

Nguyen¹,

Dung²,

Trung³

2020

Adv. sci. technol. eng. syst. j.

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This paper presents a research about the modelling of surface roughness in the grinding process. Based on the analyzed results about the surface roughness models from the previous studies, this study was performed to develop a surface roughness model in the grinding process. The surface roughness model is proposed with two hypotheses about the shape and ratio of the number of scratches of the grinding grains leaving on the workpiece surface. The first hypothesis is that the shapes of scratches of the grinding grains leave on the workpiece surface with five types including the triangle, the curved arc, the parabolic, the semi-circular, and the curved arc of a quarter circle. The second hypothesis is that the ratios of the number of the scratches with different shapes of the grinding grains leaving on the workpiece surface are the same (all are equal to 20%). This research paper discusses about the modelling of surface roughness when considering many shapes of scratches of the grinding grains left on the machining surface. This proposed model can be used to calculate the surface roughness in grinding processes of the different pairs of grinding wheels and workpieces. The developed surface roughness model has been applied to calculate the surface roughness during the grinding of SUJ2 steel using an aluminum oxide grinding wheel. Calculated surface roughness using proposed model were quite close to the experimental results. The average difference between calculated and the experimental results was about 14.84%. This study offers a promising ability to calculate the machining surface roughness in the grinding processes.

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“…The studies in this field have been carried out by many researchers, such as building models to predict surface roughness when grinding based on the analysis models of cutting thickness [2]; prediction the surface roughness when grinding with the assumption that the grits are uniformly distributed on the grinding wheel surface [3][4][5]; prediction the surface roughness when grinding through determining the average value of the depth of the cut into the machining surface of the abrasive grains [6]; applying probability theory when analyzing the cutting process of abrasive Engineering grains to predict surface roughness [7]; prediction surface roughness with the assumption that the grinding process is a mechanical -thermal equilibrium process [8]; build the relationship between surface roughness and unformed chip thickness when it was assumed that the cross section of each cut is made by an abrasive left on the surface of the workpiece with different geometric shapes (triangle, semicircular, curved, hyperbole) [1,[9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Research on calculation of grinding surface roughness

2022

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In machining processes, grinding is often chosen as the final machining method. Grinding is often chosen as the final machining method. This process has many advantages such as high precision and low surface roughness. It depends on many parameters including grinding parameters, dressing parameters and lubrication conditions. In grinding, the surface roughness of a workpiece has a significant influence on quality of the part. This paper presents a study of the grinding surface roughness predictions of workpieces. Based on the previous studies, the study built a relationship between the abrasive grain tip radius and the Standard marking systems of the grinding wheel for conventional and superabrasive grinding wheels (diamond and CBN abrasive). Based on this, the grinding surface roughness was predicted. The proposed model was verified by comparing the predicted and experimental results. Appling the research results, the surface roughness when grinding three types of steel D3, A295M and SAE 420 with Al2O3 and CBN grinding wheels were predicted. The predicted surface roughness values were close to the experimental values, the average deviation between predictive results and experimental results is 15.11 % for the use of Al2O3 grinding wheels and 24.29 % for the case of using CBN grinding wheels. The results of the comparison between the predicted model and the experiment show that the method of surface roughness presented in this study can be used to predict surface roughness in each specific case. The proposed model was verified by comparing the predicted and measured results of surface hardness. This model can be used to predict the surface hardness when surface grinding

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Surface Roughness Prediction in Grinding: a Probabilistic Approach

Cited by 7 publications

References 12 publications

Prediction of Surface Roughness When Surface Grinding C45 Steel Using CBN Grinding Wheel

Prediction of Surface Roughness When Surface Grinding C45 Steel Using CBN Grinding Wheel

Development of the Surface Roughness Model in the Grinding Processes

Research on calculation of grinding surface roughness

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