الفهرس | Only 14 pages are availabe for public view |
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. |