Surface Roughness Prediction in CNC Turning Products Using Artificial Neural Network
| المصدر: | مجلة السودان العلمية |
|---|---|
| الناشر: | مركز السودان للبحوث والدراسات الاستراتيجية |
| المؤلف الرئيسي: | Mohamed, Abdukadir Ali Mohamud (Author) |
| المجلد/العدد: | س11, ع22 |
| محكمة: | نعم |
| الدولة: |
السودان |
| التاريخ الميلادي: |
2022
|
| الشهر: | ديسمبر |
| الصفحات: | 314 - 325 |
| رقم MD: | 1548854 |
| نوع المحتوى: | بحوث ومقالات |
| اللغة: | الإنجليزية |
| قواعد المعلومات: | EcoLink, HumanIndex |
| مواضيع: | |
| رابط المحتوى: |
عدد مرات التحميل
1
| المستخلص: |
Surface roughness is a crucial machining process parameter that characterizes the caliber of the machined surface. This study attempts to analyze how cutting parameters-cutting speed (v) feed rate (f), and depth of cut (d) -affect the surface roughness during turning. An artificial neural network (ANN) model was created to accomplish this goal in order to simulate and forecast surface roughness. The ANN model's validity and accuracy are demonstrated by the strong correlation between the predicted and experimental surface roughness values. In this study, a total of 27 experimental data on steed C38 utilizing carbide P20 tools were completed. Cutting speed (V), feed rate (f), and depth of cut (a) were the input variables, and surface roughness (1) was the output variable (Ra). ANN models were created in natlab using the toolbox. |
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