Optimasi Multi Respon pada Proses End-Milling Glass Fiber Reinforced Polymer (GFRP) Dengan Menggunakan Metode Back Propagation Neural Network – Particle Swarm Optimization (BPNN-PSO)

Abstrak

The use of composite materials continues to show an increasing trend in various fields such as sports, aviation and the military. This also increases the need for knowledge about the manufacturing process of composites. One of the most widely used composite materials is glass fiber reinforced polymer (GFRP). In the process of making components made from GFRP, one of the processes that is often used is end-milling. The studies that have been carried out on the GFRP end-milling process mostly use woven fibers, while research on machining of GFRP using combo fibers has not been widely conducted. This research was conducted to determine the effect of spindle speed, feeding speed, and cutting depth, on cutting forces, surface roughness, and delamination. In addition, multi response optimization is carried out using the combined method of BPNN-PSO to obtain the most optimal combination of machining parameters. The results shows that the optimal level of cut depth, spindle speed, and feeding speed are 1 mm, 4871 rpm and 788 mm / minute, respectively.