The use of fiber reinforced composites with thermoset matrix is widespread in many areas ranging from sports products to multiple industries. This prominence, aside from the lightness of composites, can be attributed to their high mechanical resistance, good corrosion resistance, and strength density ratios that are favorable over their metal counterparts. Although their final states are approached with various single step methods, they often require secondary operations such as turning, milling or drilling. Because composite materials are not homogeneous, machining process may give rise to negative outcomes like the tearing of fibers or damages on the matrix. Composites with thermoset matrix are also brittle materials. Thus, during machining, they are processed by breaking which is not favored for production. Modified glass fiber reinforced composite (GFRP) materials, which are produced with thermoset matrix epoxy resin, are drilled in this study. Previous studies on this field had focused on the processes of turning and milling regarding the products' surface roughness. Therefore, surface roughness of holes, which were drilled according to different parameters by using L 18 matrix prepared with Taguchi's design of experiment on modified GFRP part, having 30% fiber glass, were investigated. This particular study takes on the drilling process which is also essential to manufacturing of the final products of GFRP, in the same framework. In the experiments, the influence of changing spindle speed and feed rate in different drill diameters on the inner surface of the hole, were evaluated using different cutting tools. As a result, the surface roughness of the drill, produced by the uncoated drilling bit with a diameter of 4 mm, spindle speed of 200 rpm and feed rate of 720 mm/min, was determined to be optimal.

In the competitive world today, increasing importance of conservation of energy have directed designers and engineers into search for light and mechanically high resistant material when choosing material. Glass Fiber Reinforced Plastics (GFRP) are polymer based materials made of reinforced with fiber glass. GFRPs are strong and light, showing resistance characteristics similar to metallic materials. Furthermore, the rates of the density of strength of materials are higher in comparison to metallic material. Therefore, their use has been increasing in aviation industry, wind power plant and marine applications every passing day. Assembly based process stages are used especially in aviation industry and wind power plant. In order to assemble, making a hole by drilling or CNC milling are common methods. So as to manufacture products in the required quality in making a hole in the GFRP, it is necessary to optimize cutting performance and conditions. This study aims at evaluating delamination factor in the GFRP. This study focuses on investigation, analysis and evaluation of the delamination factor in the GFRP using high precision metrology techniques that have been an indispensible part of the advanced production engineering. The parameters affecting the quality and accuracy of the workpieces are defined and experimental measurements are carried out to develop procedures in order to improve the quality and accuracy of the workpieces and machining processes.

In this study, an artificial neural networks model was established by using experimental measurement values at low speed subsonic wind tunnel of which length was 75 cm and experiment test section was 32 cm × 32 cm, and model results were compared with experimental values and then, the prediction was made for the unmeasured tunnel stream values. In the wind tunnel, when the jet velocity was 25 m/s, four tunnel velocities, 0, 5, 10, and 20 m/s were used. At the four measurement stations; x/D = 0.3, x/D = 12.5, x/D = 31.2, and x/D = 50, experimental measurements were made by using hot wire anemometer. Plain circular jet flows at x/D = 0.3 and x/D = 50 stations with average tunnel flow velocities of 7.5 m/s and 15 m/s were studied by using artificial neural networks. The data was obtained and evaluated by graphics.