Prediction of Surface Roughness considering Cutting Parameters and Humidity Condition in End Milling of Polyamide Materials

Author

Bozdemir, Mustafa

Source

Computational Intelligence and Neuroscience

Issue

Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-7, 7 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2018-06-28

Country of Publication

Egypt

No. of Pages

7

Main Subjects

Biology

Abstract EN

To know the impact of processing parameters of PA6G under different humidity conditions is important as it is vulnerable to humidity up to 7 %.

This study investigated the effect of cutting parameters to surface roughness quality in wet and dry conditions.

Artificial Neural Network (ANN) modeling is also developed with the obtained results from the experiments.

Humidity condition, tool type, cutting speed, cutting rate, and depth of cutting parameters were used as input and average surface roughness value were used as output of the ANN model.

Testing results showed that ANN can be used for prediction of average surface roughness.

American Psychological Association (APA)

Bozdemir, Mustafa. 2018. Prediction of Surface Roughness considering Cutting Parameters and Humidity Condition in End Milling of Polyamide Materials. Computational Intelligence and Neuroscience،Vol. 2018, no. 2018, pp.1-7.
https://search.emarefa.net/detail/BIM-1130782

Modern Language Association (MLA)

Bozdemir, Mustafa. Prediction of Surface Roughness considering Cutting Parameters and Humidity Condition in End Milling of Polyamide Materials. Computational Intelligence and Neuroscience No. 2018 (2018), pp.1-7.
https://search.emarefa.net/detail/BIM-1130782

American Medical Association (AMA)

Bozdemir, Mustafa. Prediction of Surface Roughness considering Cutting Parameters and Humidity Condition in End Milling of Polyamide Materials. Computational Intelligence and Neuroscience. 2018. Vol. 2018, no. 2018, pp.1-7.
https://search.emarefa.net/detail/BIM-1130782

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1130782