Optimization Of Tribological Properties Of Aluminium Honeycomb Reinforced Polymeric Composites Using Grey Based Fuzzy Algorithm

In this research two composite materials were fabricated by using two matrix materials and one common reinforcement material. The two matrix materials were Polypropylene and Nylon 6. Reinforcement material was Aluminium honeycomb core. Compression moulding machine was used for the fabrication of these composite materials. Two body abrasive wear experiments were conducted by using a pin-on-disc Tribotester under dry sliding condition and at room temperature. The design process parameters for two-body abrasive wear test were normal load, sliding velocity, sliding distance and abrasive paper grit size. The output responses were Coefficient Of Friction (COF) and Specific Wear Rate (SWR). The design of experiments is based on L9Taguchi orthogonal array. Grey fuzzy logic algorithm was used for the optimization of input process parameters. For polypropylene composite material the highest Grey Fuzzy Reasoning Grade (GFRG) is obtained at 30 N normal load, 0.523 m/s sliding velocity, 450 m sliding distance, 320 grit size of abrasive paper and these are the optimum level of process parameters. For nylon composite material highest GFRG is obtained at 30 N normal load, 1.046 m/s sliding velocity, 150 m sliding distance, 400 grit size of abrasive paper and these are the optimum level of process parameters. The optimum level of process parameters were also validated with conformation experiments.