Surface roughness evaluation of ferrous alloys by using predictive model
العناوين الأخرى
تقييم خشونة السطوح لسبائك حديدية مشغلة بالخراطة باستخدام نموذج استنباطي إحصائي
مقدم أطروحة جامعية
Abu Mandil, Rafat Salim Abd Allah
مشرف أطروحة جامعية
al-Tai, Abbas Jawad
Abu Saa, Fathi
الجامعة
جامعة أم درمان الإسلامية
الكلية
كلية العلوم الهندسية
القسم الأكاديمي
قسم الهندسة الميكانيكية
دولة الجامعة
السودان
الدرجة العلمية
ماجستير
تاريخ الدرجة العلمية
2008
الملخص الإنجليزي
There are different machining parameters have effects on surface roughness, but those effects have not been quantified.
several researches studied the effects of different combinations of machining parameters on surface roughness to achieve an accurate predictive models for surface roughness, and still more researches has to be conducted, hence, this research was carried out.
spare parts for textile machines need to be manufactured with high surface finish and close tolerances to reduce friction heat and vibration.
To manufacture these parts, four types of steel available locally has been chosen, to reduce maintenance cost by substituting imported parts.
Four different types of steels were used (AISI C1040 carbon steel, PH14-8MO nickel-chromium alloy steel AISI C1020 carbon steel, and 5-35-NCI gray cast iron) with HRB hardness 115,101,95, and 90 respectively.
Material bars were machined by turning, using high precision URPE lathe model 4-M.
Emulsion oil RP–0040596 was used as a coolant and Cemented carbide insert tool was used through the work.
Three parameters (cutting speed, feed rate, and depth of cut) were used independently and statistical analysis of variances was performed and roughness of machined samples were measured.
It has been shown that AISI C1040 carbon steel gave the best correlation with surface roughness all over the experiments.
Lower feed rate and lower depth of cut resulted in better surface roughness.
In a certain range of cutting speed variation the lower cutting speed resulted in better surface roughness due to forming of built-up edge.
This result contradicts the known trend of roughness, So, a second round of experiments were executed, utilizing Taguchi experimental design to determine the optimal machining parameters for a desired surface roughness, and to identify the impact of various parameters on an output and to determine the combination of parameters to reduce the variability in that output.
CNC lathe model LTC – 20B has been utilized in second round of experiments and statistical software program, SPSS version 12, was employed in regression prediction model, and two prediction equations for roughness simulation has been obtained.
التخصصات الرئيسية
الموضوعات
عدد الصفحات
74
قائمة المحتويات
Table of contents.
Abstract.
Introduction.
Chapter One : Literature review.
Chapter Two : Experimental work and result analysis.
Chapter Three : Discussion, conclusion and suggestions.
References.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Abu Mandil, Rafat Salim Abd Allah. (2008). Surface roughness evaluation of ferrous alloys by using predictive model. (Master's theses Theses and Dissertations Master). Omdurman Islamic University, Sudan
https://search.emarefa.net/detail/BIM-363040
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Abu Mandil, Rafat Salim Abd Allah. Surface roughness evaluation of ferrous alloys by using predictive model. (Master's theses Theses and Dissertations Master). Omdurman Islamic University. (2008).
https://search.emarefa.net/detail/BIM-363040
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Abu Mandil, Rafat Salim Abd Allah. (2008). Surface roughness evaluation of ferrous alloys by using predictive model. (Master's theses Theses and Dissertations Master). Omdurman Islamic University, Sudan
https://search.emarefa.net/detail/BIM-363040
لغة النص
الإنجليزية
نوع البيانات
رسائل جامعية
رقم السجل
BIM-363040
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
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