Article ; Online: Performance optimization in electro- discharge machining using a suitable multiresponse optimization technique
Decision Science Letters, Vol 6, Iss 3, Pp 283-
2017 Volume 294
Abstract: In the present research work, four different multi response optimization techniques, viz. multiple response signal-to-noise (MRSN) ratio, weighted signal-to-noise (WSN) ratio, Grey relational analysis (GRA) and VIKOR (VlseKriterijumska Optimizacija I ... ...
Abstract | In the present research work, four different multi response optimization techniques, viz. multiple response signal-to-noise (MRSN) ratio, weighted signal-to-noise (WSN) ratio, Grey relational analysis (GRA) and VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian) methods have been used to optimize the electro-discharge machining (EDM) performance characteristics such as material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR) simultaneously. Experiments have been planned on a D2 steel specimen based on L9 orthogonal array. Experimental results are analyzed using the standard procedure. The optimum level combinations of input process parameters such as voltage, current, pulse-on-time and pulse-off-time, and percentage contributions of each process parameter using ANOVA technique have been determined. Different correlations have been developed between the various input process parameters and output performance characteristics. Finally, the optimum performances of these four methods are compared and the results show that WSN ratio method is the best multiresponse optimization technique for this process. From the analysis, it is also found that the current has the maximum effect on the overall performance of EDM operation as compared to other process parameters. |
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Keywords | Multi response optimization techniques ; MRR ; TWR ; SR ; ANOVA technique ; Mathematics ; QA1-939 ; Science ; Q ; Analysis ; QA299.6-433 ; Business mathematics. Commercial arithmetic. Including tables ; etc. ; HF5691-5716 |
Subject code | 621 |
Language | English |
Publishing date | 2017-06-01T00:00:00Z |
Publisher | Growing Science |
Document type | Article ; Online |
Database | BASE - Bielefeld Academic Search Engine (life sciences selection) |
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