الفهرس 
Chapter 1: IntroductionOnly 14 pages are availabe for public view
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Abstract
CNC technology revolutionized production by eliminating tasks that were labor- intensive, costly, and prone to errors. This technological breakthrough lowered the cost and time needed to produce complex products while reducing human errors. Taguchi’s parameters design provides a systematic way to optimize process performance, quality, and cost.
Quality and productivity are essential in the current manufacturing market and economic. Metal Matrix composites compounds are synthetic materials that have an increasingly used in various industrial sectors. However, cutting MMCs is a challenge
,because of high hardness and abrasiveness of the reinforcements. Which has a bad effect in product surface quality, tool wear, and consequently higher processing costs. Moreover, the early failure of cutting tools requires frequent tool replacements.
Gap analysis begins with the current state followed by defining the future state that includes all Factors affecting the current study and its characteristics that need improvement. This stage involved a thorough examination of most previous studies in the field, with a focus on the experimental, analytical, and model-based aspects of prediction and optimization.
The main objectives of this work are to examine the cutting parameters of the end milling . The reinforcements used in this study are ceramic nanoparticles TiO2, Al2O3, and SiO2. The composite is produced using the stir-casting process in an electric melting furnace. The experimental study uses different weight percentages of nanoparticle. The Taguchi optimization process is used to optimize the cutting parameters with different number of cutting edges of high-speed steel end mill. The milling parameters were studied under various weight percentages of TiO2, Al2O3, and SiO2, rotational speed, cutting speed, number of the cutters flutes , feed rate, and depth of cut.
The goal of this research work is to propose new strategies for understating, modeling, and optimizing surface roughness, cutting forces, and hardness during slot milling of Al-MMCs. The goal of this work is the surface roughness minimization and force cutting, and maximization of metal removal rate and hardness.
In the CNC milling process, Taguchi, and response surface methods (RSM) were applied to minimize surface roughness and cutting forces and maximize the product hardness. Taguchi’s approach, which uses the signal-to-noise ratio and an ANOVA
analysis of the surface finish, was used to select the optimum milling process parameters.
Response surface methodology (RSM) was used to establish quadratic relationships between the cutting parameters and surface roughness in a second-order model. The optimal levels of the milling parameters were determined by measuring the surface roughness of the machined surfaces. Based on Taguchi, ANOVA, and RSM analysis, the end milling process can be optimized to improve surface finish quality and machining productivity.
The experimental results, based on both the signal-to-noise ratio and the arithmetic average, indicate that the rotational speed and cutting speed are the most influential factors affecting the average surface roughness at 99%, 95%, and 90% confidence levels, for all tested composite materials ,also these two factors significantly remarkable effect in the cutting forces for the same confidence levels.
At optimal parameter levels for Al-MMC/TiO2, the highest metal removal rate is 25.72 cm3/min, and the average surface roughness is 2.81 µm, and best value of cutting forces is 131.651 N. Validation of RSM models indicates that the average percentage deviation in cutting forces, material removal rate and surface roughness, based on S/N ratio values are 5.19 %, 2.35%, and 10.20% respectively.
To evaluate the models under consideration, several performance indicators such as average percentage of model correctness, Square Root of the Average Squared Residual (SRA), Average Absolute Residual (AAR), and Root Mean Square Error (RMSE) were utilized.