Abstract
Study of process parameter and their selection is very important in the process performance point of view; this issue is attempted mostly by Taguchi method. However, Taguchi approach can be applied only to single-objective problem, and in case of multi-objective problem, it gives different levels and it becomes difficult to interpret these results. Principal component analysis (PCA) transforms the set of uncorrelated components to get the optimum level of combination for all the responses. In this paper, PCA is applied to a case study having three responses, i.e., change in surface roughness, tangential cutting force, and normal magnetic force. The levels of parameters obtained by PCA show the improved results for responses than those obtained by Taguchi method.
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Gunjal, S.B., Pawar, P.J. (2020). Optimization of Magnetic Abrasive Finishing Process Using Principal Component Analysis. In: Venkata Rao, R., Taler, J. (eds) Advanced Engineering Optimization Through Intelligent Techniques. Advances in Intelligent Systems and Computing, vol 949. Springer, Singapore. https://doi.org/10.1007/978-981-13-8196-6_43
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DOI: https://doi.org/10.1007/978-981-13-8196-6_43
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