Cutting tests were conducted to medium carbon steel using HSS tools with cutting fluid. The experimental design used was based on response surface methodology (RSM) using a central composite design. Chips were collected at different machining conditions and thickness and microhardness measurements taken and analyzed using “DESIGN EXPERT 7” experimental design software. Mathematical models of the responses (thickness and microhardness) as functions of the conditions (speed, feed, and depth of cut) were obtained and studied. The resultant second-order models show chip thickness increases when increasing feed and speed, while increasing depth of cut resulted in a little effect on chip thickness. Chip microhardness increases with increasing depth of cut. It also increases with increasing speed and feed up to a certain level beyond which further increases cause a drop in microhardness.

This research aims to study the effect of using the anodizing process on the corrosion rate, mechanical properties as well as the fatigue life for aluminum alloy (7075-T73), which is one of the most commonly used aluminum alloy in production of aircrafts, vehicles and ships structures. The anodizing process was employed through using sulfuric acid for time (20) min in a salty atmosphere. The mechanical properties and fatigue life of the AA7075-T73 were obtained before and after the anodizing process. All the results were listed in detailed tables and figures for comparison purpose. Generally, these results showed a decrease in corrosion rate by (155.06%) in comparison with untreated, an increase in hardness by (21.54%) and a slight decrease in fatigue life by (7.7%) due to anodizing for a time of 20 min at the stress level of (σa = 491.10 MPa). It was concluded that this technique could be applied on other aluminum alloys in order to know the magnitude of change in the mechanical characteristics and their fatigue life.

This paper represents an experimentalattempt to predict the influence of CO2-MAG welding variables on the shape factors of the weld joint geometry. Theinput variables were welding arc voltage, wire feeding speed and gas flow rate to investigate their effects on the shape factorsof the weld joint geometry in terms of weld joint dimensions (bead width, reinforcement height, and penetration). Design of experiment with response surface methodology technique was employed to buildmathematical models for shape factors in terms of the input welding variables. Thepredicted models were found quadratic type and statistically checked by ANOVA analysis for adequacy purpose. Also, numerical and graphical optimizations were carried out to determine the optimum values for all responses and input variables. The optimum values of the voltage, wire feeding speed, gas flow rate, WPSF, and WRFF are (20 Volt), (153 cm/min), (10 L/min), (5.222), and (3.970), respectively. And, a good agreement was found between the experimental and predicted results. The weld joint efficiency was found (73%) at the optimum conditions.  

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Cutting tests were conducted to longitudinally turn low carbon steel using HSS tools with cutting fluid. The experimental design used was based on response surface methodology (RSM) using a central composite rotatable (CCD) design. The primary cutting tests confirmed the use of proper specimen design with length to diameter ratio (L/D) of 2 in the subsequent cutting tests of this research. Further cutting tests were carried out to turn low carbon steel with L/D=2 to determine the effect of using different cutting conditions on the surface roughness and roundness error (out of roundness) of the machined surfaces. At the end of each cutting test, the surface roughness and roundness error measurements were taken and analyzed using “DESIGN EXPERT 8” experimental design software. Mathematical models of responses (surface roughness and roundness error) as functions of the conditions (cutting speed, feed, and depth of cut) were obtained and studied. A quadratic predicted model for surface roughness showed that the feed, cutting speed and their squares and interactions were more effective than the depth of cut because of its little influence on the surface roughness. Also, the resultant two-factor interaction (2FI) model for roundness error exhibited that cutting speed, feed and the interaction of feed and speed were significant parameters, while the depth of cut had no effect. The predicted models indicated that at higher cutting speed and various feed levels, both responses decreased, resulting in a smooth machined surface with lower roundness error. But, both models exhibited that at lower cutting speed and higher feeds, the surface roughness and roundness error increased, producing a rough machined surface with higher out of roundness error.