The weight of gears is an important issue for high performance of the machine elements. Thus, the design of the gear pairs with respect to the minimum weight is an important and attractive subject to study. Various analytical and heuristic approaches were utilized to optimize the weight of gears in previous studies. In this study, the problem of gear optimization as per the minimum weight was solved with Grey Wolf Optimizer (GWO). GWO is a meta-heuristic optimization method that stands out with its successful performance in engineering applications. In this study, the performance of GWO was investigated in the case of constituting a spur gear with respect to minimum weight for the first time. Compared with the previous studies, the results obtained in the study show that it is possible to design a lighter gear with GWO.

This study aims to investigate the mechanical properties of Functionally Graded Lattice Structures (FGLSs) and to determine their industrial application possibilities through additive manufacturing. For this purpose, lattice structures with uniform and horizontal, vertical and radially graded configurations are designed using auxetic unit cells were fabricated with RGD720 photopolymer resin using Material Jetting. FGLSs are compared with uniform structures in regards with deformation behavior, structural strength and energy absorption. The results showed that the most significant deviation in the strut diameters of the uniform lattice structures was seen in the rotation lattice structure at 8.2%. The lowest deviation was seen in the chiral structure, which deviated by 5.4%. The lowest deviations (between 3.4% and 9%) in FGLSs were obtained in chiral structures. The highest relative density value (0.3049 g/cm³) among all configurations was observed in the vertically graded chiral structure. The lowest relative density value (0.1865 g/cm³) was obtained in uniform re-entrant structures. According to the compression test results, the highest compressive stress (2.61513 MPa) and elastic modulus (84.63192 MPa) were formed in the rotation structure. The maximum energy absorption capacity value (19.381 KJ) and the maximum specific energy absorption value (3649.905 KJ/kg) were obtained in the uniform chiral structure.

The design of gears with a minimum weight is an optimization problem that has been widely discussed in the literature. Various recent metaheuristic optimization methods, along with the conventional methods, have produced successful results for design optimization problems. In this study, a comprehensive investigation was conducted into the solution of the spur gear design problem in metaheuristic optimization methods. The artificial algae algorithm, artificial bee colony and whale optimization algorithm were applied to the problem for the first time. The grey wolf optimizer and particle swarm optimization were also applied. The results were compared with the performance of the genetic algorithm, simulating annealing and particle swarm optimization, applied in previous studies. A statistical evaluation of these methods applied under the same conditions was carried out in terms of stability. It was shown that the new methods demonstrated significantly improved performance in solving the gear design problem compared to existing methods.

In this experimental study, composite samples containing silicon are produced with powder metallurgy technique by sintering under argon atmosphere. The effect of cutting speeds, feed rates and different cutting tool types on cutting forces and surface roughness are investigated in the face milling operation of silicon carbide particle reinforced aluminium metal matrix composites. Machining operations are conducted using coated and uncoated tools. Main cutting force (Fx) and surface roughness (Ra) are measured for at four different cutting speeds (300, 350, 400 and 450 m/min) and three different feed rates (0.1, 0.15, 0.20 mm/tooth) and two depth of cut (0.5, 1 mm). As a result of experimental evaluation for coated and uncoated tools, main cutting force increased with increasing feed rate and depth of cut whereas, it is decreased significantly by higher cutting speed. On the other hand, Al-SiC produces the worst surface finish with increasing feed rate and depth of cut in the uncoated tools whereas, the surface roughness in the coated tools are decreased under the same cutting conditions. The best surface roughness is obtained with increasing cutting speed for both uncoated and coated tools. Key words: Metal matrix composite, face milling, machining, cutting forces, surface roughness.