Influence of Cutting Parameters on Surface Roughness during Milling AISI 1045 Steel

Trung, Do Duc

doi:10.24874/ti.969.09.20.11

Cited by 23 publications

(17 citation statements)

References 5 publications

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“…The Johnson transformation was also successfully applied to improve the accuracy of surface roughness model when turning 3X13 steel [21], and when miiling AISI 1045 steel [22]. In this research, these two transformations will also be applied with the desire to improve the accuracy of the surface roughness model when grinding 65G steel.…”

Section: Resultsmentioning

confidence: 99%

Influence of Cutting Parameters on Surface Roughness in Grinding of 65G Steel

Trung¹

2021

Tribol. Ind.

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This article presents an experimental research in the grinding the 65G steel. The workpiece velocity, feed rate, and cutting depth are selected as the input parameters for each experiment. The experiments were performed according to a Box-Behnken matrix consisting of 15 experiments. ANOVA analysis results have determined the influence of the input parameters and the interaction between them on the surface roughness. A surface roughness model in the form of quadratic polynomial was constructed. Two data transformations including Box-Cox and Johnson were applied to construct two new surface roughness models. The comparison of three surface roughness models was conducted. The comparison results show that the model using the Johnson transformation has the highest accuracy, the model using the Box-Cox transformation has the accuracy ranked the second position and the model without data transformation had the lowest accuracy.

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Section: Resultsmentioning

confidence: 99%

Influence of Cutting Parameters on Surface Roughness in Grinding of 65G Steel

Trung¹

2021

Tribol. Ind.

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“…The values of selected input parameters according to the cutting tool manufacturer's recommendation and by study No. [25] are presented in Table 2.…”

Section: Methodsmentioning

confidence: 99%

Study on model for cutting force when milling SCM440 steel

Thien

Trung

2021

Eureka: PE

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This article presents empirical study results when milling SCM440 steel. The cutting insert to be used was a TiN coated cutting insert with tool tip radius of 0.5 mm. Experimental process was carried out with 18 experiments according to Box-Behnken matrix, in which cutting speed, feed rate and cutting depth were selected as the input parameters of each experiment. In addition, cutting force was selected as the output parameter. Analysis of experimental results has determined the influence of the input parameters as well as the interaction between them on the output parameters. From the experimental results, a regression model showing the relationship between cutting force and input parameters was built. Box-Cox and Johnson data transformations were applied to construct two other models of cutting force. These three regression models were used to predict cutting force and compare with experimental results. Using parameters including coefficient of determination (R-Sq), adjusted coefficient of determination (R-Sq(adj)) and percentage mean absolute error (% MAE) between the results predicted by the models and the experimental results are the criteria to compare the accuracy of the cutting force models. The results have determined that the two models using two data transformations have higher accuracy than model not using two data transformations. A comparison of the model using the Box-Cox transformation and the model using the Johnson transformation was made with a t-test. The results confirmed that these two models have equal accuracy. Finally, the development direction for the next study is mentioned in this article

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“…The parameters including spindle speed, feed rate, and cutting depth have been selected as the three input parameters of the experimental process. These three parameters can all be adjusted quickly by the worker and have also been selected as the experimental input parameters in many studies [28]. The values of these parameters are chosen to be suitable when milling 060A4 steel with HSS cutting tools as well as suitable for the ability of their value adjustment of the experimental machine.…”

Section: Fig 1jlvh320b Vertical Milling Machinementioning

confidence: 99%

Optimization of Milling Process by Taguchi-PSI Method

Anh

Tuan²,

Quang³

et al. 2021

E3S Web Conf.

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060A4 steel (Chinese standard) is a steel with good machinability, which is very popularly used in mechanical engineering. Therefore, the study of solutions for improvement of quality and productivity when machining this steel type has great technical and economic significance. In this study, the multi-objective optimization process has been performed when milling this steel type on a vertical milling machine. The cutting tool is a face milling cutter made of High Speed Steel (HSS) material. The effect of spindle speed, feed rate, and cutting depth on surface roughness has been found. The combination of the Taguchi method and PSI method has been applied to determine the optimal value of three input parameters to simultaneously ensure the two criteria of the minimum surface roughness and the maximum Material Removal Rate (MRR). The works which will be done by the authors of this article in the near future has also been presented in the last part of this study.

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Influence of Cutting Parameters on Surface Roughness during Milling AISI 1045 Steel

Cited by 23 publications

References 5 publications

Influence of Cutting Parameters on Surface Roughness in Grinding of 65G Steel

Influence of Cutting Parameters on Surface Roughness in Grinding of 65G Steel

Study on model for cutting force when milling SCM440 steel

Optimization of Milling Process by Taguchi-PSI Method

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