ABSTRACT

 This work presents the assessment of aluminum alloy 356 with cow horn composite as a machining material. In otherto enable manufacturers to maximize their gains from utilizing hard turning, an accurate model ofthe process must be constructed. In course ofthis work, a mathematical model was developed to relate the material removal rate (MRR), tool wear ratio (TWR) and surface roughness (Ra) to machining parameters (feed rate, depth of cut and cutting speed). To achieve this, A356/cow horn particles (CHp) composite was adopted from Ochieze, 2017. A design of experiment was generated using the optimal custom design techniques in Response Surface Methodology (RSM) from the Design Expert Software 11.0. after the optimization, the results from the ANOVA tables ofthe tool wear, surface roughness and material removal rate show some models are significant with the probability value (P-value) 0.0203, 0.0412. The results of the analysis of variance (ANOVA) indicate that the proposed mathematical models, can adequately describe the performance within the limits ofthe factors being studied. It was also observed that the cutting speed plays a dominant role in tool wear rate (TWR) and surface roughness (Ra) while the depth of cut has the least influence on the tool wear rate (TWR) and surface roughness (Ra). Finally, the good surface quality with the minimum tool wear can be achieved when cutting speed and feed rate are set nearer to their middle level (900rpm, 0.25 rev/mm) and depth of cut is at high level of the experimental range (1.5mm). In summary, in order to enable manufacturers to maximize their gains in utilizing hard turning ofAACHC, they should employ the optimized cutting parameters.