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International Journal of Engineering، جلد ۳۱، شماره ۱، صفحات ۳۲-۳۷
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| عنوان فارسی |
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| چکیده فارسی مقاله |
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| کلیدواژه‌های فارسی مقاله |
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| عنوان انگلیسی |
Predictions of Tool Wear in Hard Turning of AISI4140 Steel through Artificial Neural Network, Fuzzy Logic and Regression Models |
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| چکیده انگلیسی مقاله |
The tool wear is an unavoidable phenomenon when using coated carbide tools during hard turning of hardened steels. This work focuses on the prediction of tool wear using regression analysis and artificial neural network (ANN).The work piece taken into consideration is AISI4140 steel hardened to 47 HRC. The models are developed from the results of experiments, which are carried out based on Design of experiments (Response surface methodology). The cutting speed, feed and depth of cut are taken as the inputs and the wear is the output. The results reveal that the ANN provides better accuracy when compared to Regression analysis. |
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| کلیدواژه‌های انگلیسی مقاله |
AISI4140, ANN, Hard Turning, Regression |
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| نویسندگان مقاله |
Natesan Kanthavelkumaran |
Mechanical Engineering, Arunachala College of Engineering for Women, Kanyakumari, Tamilnadu, India
Dinakaran D |
Mechanical Engineering, Hindustan University, Chennai
Rajeev D |
Mechanical Engineering, Mar Ephraem College of Engineering and Technology
Austin N |
Mechanical Engineering, Mar Ephraem College of Engineering and Technology
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| نشانی اینترنتی |
http://www.ije.ir/article_73088_895298fb7dc313c53d1ce64054295bbc.pdf |
| فایل مقاله |
اشکال در دسترسی به فایل - ./files/site1/rds_journals/409/article-409-2061931.pdf |
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| زبان مقاله منتشر شده |
en |
| موضوعات مقاله منتشر شده |
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