The Optimization of Cutting Parameters Using Metal Removal Rate and Surface Roughness Responses
| المصدر: | مجلة القلعة |
|---|---|
| الناشر: | جامعة المرقب - كلية الآداب والعلوم بمسلاته |
| المؤلف الرئيسي: | Alwaer, Khaled S. M. (Author) |
| مؤلفين آخرين: | El Musbahi, Mustafa.A. (Co-Author) |
| المجلد/العدد: | ع7 |
| محكمة: | نعم |
| الدولة: |
ليبيا |
| التاريخ الميلادي: |
2017
|
| الشهر: | يونيو |
| الصفحات: | 652 - 670 |
| رقم MD: | 891622 |
| نوع المحتوى: | بحوث ومقالات |
| اللغة: | الإنجليزية |
| قواعد المعلومات: | HumanIndex |
| مواضيع: | |
| رابط المحتوى: |
عدد مرات التحميل
4
| المستخلص: |
The accuracy of surface roughness is affected by many factors, like depth of cut, cutting speed, feed rate, and the microstructure of work piece, the cutting tool geometry and the rigidity of the Lathe machine. When the working parameters are not selected properly, the tool wears quickly and broken. This causes economical losses like spoiling surface quality of the work piece. There are many parameters that effect on the metal removal rate (MRR) and surfaces roughness (Ra). In this study six of these parameters have been investigated. These parameters are : cutting speed, depth of cut, feed rate, nose radii, insert shape and insert type. This study describes the applications of Fuzzy logic analysis coupled with Taguchi methods to optimise the precision and accuracy of the turning process. A Fuzzy logic system is used to investigate the relationships between the machining precision and accuracy for determining the efficiency of design parameter of the Taguchi static function experiments. From the Fuzzy inference process, the optimal process conditions for the turning process can be easily determined as cutting speed 2500 rpm, feed rate 0.1 mm/rev, depth of cut 2mm, nose radii 1.2 mm, insert shape 35 degree , and coated insert type. Furthermore, a conformation experiment of the optimal process shows that the target performance characteristics is improved to achieve more desirable level. The use of these mentioned statistical techniques have helped to increase the metal removal rate by 1 %, and multi-response performance index (MRPI) by increase 20 %. |
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