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Prediction of Optimal Process Parameters in Hardfacings Obtained by Using Submerged Arc Welding Technique

Year 2016, Volume: 1 Issue: 1, 25 - 35, 01.06.2016

Abstract

In this study, hardfacings were obtained by using with submerged arc welding powders including different high carbon ferrochromium (4-16 wt.%) and currents from 400 A to 550 A. In order to determine the optimal process parameters in hardfacings, we presented two neural network based predictions with ANN algorithm for chromium and carbon percentages, secondary dendrite arms spacing, cooling rates, macrohardness, and wear loss. The results of ANN performance were presented at two sets of FeCr (wt.%) and net heat inputs in detail. Similarly, two ANN architectures were preferred to obtain the most accurate results. The performance evaluations of the networks were carried out by using Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and the Coefficient of Correlation, R2, for all models. The models having architecture of 2-15-3 and 2-23-4 were found to be optimal after these criteria. The results showed that the ANNs which helped to decrease number of experimental tests had an acceptable degree of accuracy and great reliability.

Year 2016, Volume: 1 Issue: 1, 25 - 35, 01.06.2016

Abstract

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Details

Other ID JA62KV44EF
Journal Section Articles
Authors

Mustafa Kaptanoğlu This is me

Akın Odabaşı This is me

Zafer Aydoğmuş This is me

Publication Date June 1, 2016
Submission Date June 1, 2016
Published in Issue Year 2016 Volume: 1 Issue: 1

Cite

APA Kaptanoğlu, M., Odabaşı, A., & Aydoğmuş, Z. (2016). Prediction of Optimal Process Parameters in Hardfacings Obtained by Using Submerged Arc Welding Technique. Harran Üniversitesi Mühendislik Dergisi, 1(1), 25-35.