This paper presents the influence of cutting parameters like cutting speed, feed rate, drill diameter, point angle and clearance angle on the surface roughness and circularity deviation of Alluminium alloys during drilling on CNC vertical machining center. A plan of experiments based on Taguchi method has been used to acquire the data. An orthogonal array, signal to noise (S/N) ratio and analysis of variance (ANOVA) are employed to investigate machining characteristics of Alluminium alloys using HSS twist drill bits of variable tool geometry and maintain constant helix angle of 45 degrees. Confirmation tests have been carried out to predict the optimal setting of process parameters to validate the proposed approach and obtained the values 3.7451µm, 0.1076 mm for surface roughness and circularity deviation respectively. Finally, the output results of Taguchi method fed as input to the AHP and TOPSIS. The results generated in both AHP and TOPSIS suggests the suitable alternative of aluminum alloy, which results in better surface roughness and less error in circularity.
Drilling is a hole making process on machine components at the time of assembly work, which are identify everywhere. In precise applications, quality and accuracy play a wide role. Nowadays’ industries suffer due to the cost incurred during deburring, especially in precise assemblies such as aerospace/aircraft body structures, marine works and automobile industries. Burrs produced during drilling causes dimensional errors, jamming of parts and misalignment. Therefore, deburring operation after drilling is often required. Now, reducing burr size is a serious topic. In this study experiments are conducted by choosing various input parameters selected from previous researchers. The effect of alteration of drill geometry on thrust force and burr size of drilled hole was investigated by the Taguchi design of experiments and found an optimum combination of the most significant input parameters from ANOVA to get optimum reduction in terms of burr size by design expert software. Drill thrust influences more on burr size. The clearance angle of the drill bit causes variation in thrust. The burr height is observed in this study. These output results are compared with the neural network software @easy NN plus. Finally, it is concluded that by increasing the number of nodes the computational cost increases and the error in nueral network decreases. Good agreement was shown between the predictive model results and the experimental responses.
Burr formation during machining process is a vital role in the assembly lines, even though it is a non value added process but also care should be taken while machining due to non avoiding output generated at the end of material removal process. At present almost all manufacturing sectors faces lot of problems due to these issues and invest more money towards deburring still advanced manufacturing methods available. So, complete burr removal is not possible and only thing is reducing utmost by applying better optimizing techniques, to develop good mechanization methods, selecting optimum process parameters and their conditions. The aim this paper deals about research methods implemented by earlier authors on burr formation especially in drilling. The reason why the present authors selected the drilling is number of automotive and aircraft engineers struggling during structural building works because of these burrs wherever precise measurement needed. In this connection, the authors concentrate their study on previous researcher works related to investigations on experimentation, developing new theoretical mechanisms to minimize burrs, adapt a new technologies available to modify drill bit geometries such that improvement in the minimization of burrs. Finally found that research contributions by changing their drill bit geometry and cutting process parameters have been focused on utilizing the methodologies, changing time to time. In analyzing the performance characteristics with that of input process parameters, several mathematical and empirical models were developed by many researchers so far in their works. Efforts have been made in the direction of optimization of process parameters in drilling for minimizing burr size.
In the present work to validate the experimental results as per Taguchi based grey relational analysis by considering L27 orthogonal array corresponding to five factors with three levels and obtained optimal combination of input parameters to minimize the output responses during drilling process which is most important finishing operation required in the structural assembly works where we found application of Al-Mg-Si alloys, Deform-3D software is implemented and found good feasibility with that of experimental results.
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