الفهرس 
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Abstract
In this research, experiments were conducted to study the effect of different
variables on the surface grinding process. Several experiments were conducted
to study the effect of five variables: cutting speed, feed rate, depth of cut,
cooling method and surface hardening on the surface roughness resulting from
the machining process and the cutting forces as indicators of efficiency and
effectiveness in terms of quality and cost for this process. Mild carbon steel
was used, which is one of the commonly used materials in manufacturing
processes.
In this study, the standard orthogonal Taguchi matrix was used in the design
of experiments due to the large number of variables used and their levels.
Minitab 17 was used to identify the main influences in this process. Then,
analysis of variance (ANOVA) was conducted to find the dependent variables
that affect the characteristics of the cutting process, regression analysis was
conducted to find out the relationship between the different factors and responses, and then using the analysis signal to noise ratio test (S/N) to
determine the best conditions for the cutting process.
In addition, this work presents the modeling of grinding process by finite
element method in an orthogonal machining process for mild carbon steel
(ASTM A36) using the computer software program (Abaqus/CAE). The aim
was to simulate and model the cutting process, extract cutting forces, and
predict surface roughness due to its vital role in machining processes. A
comparison was made between the results extracted from the model with those
obtained from practical experiments to verify the validity of the simulation
results.It was found that the best input grinding parameters collection group for the
ASTM A36 mild carbon steel involves the cutting speed of 26 m/sec, feed rate
of 2.5 m/min, and the depth of cut of 0.1 mm combined with a high quantity
lubricant. The surface roughness decreases if the material subjected to surface
hardening before machining , and the results shows a significant decrease in
Ra by 5% up to 30%. Also, the results showed that there is an effect of the
cooling efficiency on the behavior of the grains which lead to better surface
quality.
KEYWORDS
Optimization of surface grinding parameters, Taguchi, ANOVA, finite element.