Speaker
Description
In this work, sparking electro-discharge machining (EDM) process parameters are optimized by using multiple criteria decision-making (MCDM) methods. The workpiece utilized for the investigation was LM25 aluminum alloy reinforced with Vanadium carbide (VC), processed through a stir casting technique. The EDM process parameters that have been considered in this work are current expanded by high voltage, pulse-on-time, pulse-off-time, and the weight ratio of VC, with the effects of each variable and their combinations on the performance metrics of EDM like material removal rate, electrode wearing rate, and surface roughness. In this study, four MCDM methodologies were applied to evaluate EDM performance. Then, the obtained MCDM scores were compared using two different objective verification mechanisms. In this case, the TOPSIS technique delivered the best-desired results relative to VIKOR method, response surface method (RSM), and teaching-learning based optimization (TLBO) method. Also, the RSM method is simpler than the other methods, though it produced nearly identical results as the sophisticated MDCM method.
Keywords: Electro-discharge machining; Response surface method; Multiple criteria decision-making; Teaching-learning based optimization; VIKOR method
| Conference Topic Areas | Track8: Design Optimization, Additive Manufacturing Technologies & Applications |
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