In this paper, wire electrical discharge machining of D3 tool steel is studied. Influence of pulse-on time, pulse-off time, peak current and wire speed are investigated for MRR, dimensional deviation, gap current and machining time, during intricate machining of D3 tool steel. Taguchi method is used for single characteristics optimization and to optimize all four process parameters simultaneously, Grey relational analysis (GRA) is employed along with Taguchi method. Through GRA, grey relational grade is used as a performance index to determine the optimal setting of process parameters for multiobjective characteristics. Analysis of variance (ANOVA) shows that the peak current is the most significant parameters affecting on multi-objective characteristics. Confirmatory results, proves the potential of GRA to optimize process parameters successfully for multi-objective characteristics.Keywords ANOVA Á D3 tool steel Á Grey relational analysis Á Multi-objective optimization Á Taguchi method Á Wire electrical discharge machining (WEDM)
The present research study deals the Wire electrical discharge machining (WEDM) process for High carbon high-chromium steel (D3) with multi-parametric optimization based on the Taguchi method and desirability function analysis. Experiments were carried out based on an L9 orthogonal array. The effect of process parameter such as pulseon time (Ton), pulse-off time (Toff), current (IP) and wire speed (Ws) were analyzed on the performance measures such as material removal rate, dimensional deviation, gap current and machining time. The optimum cutting conditions are obtained by Taguchi method and desirability function. The analysis of variance (ANOVA) is applied to investigate the effect of input process parameters. Finally, the confirmation experiment was carried out for the optimal machining parameters, and the betterment has been proved.
Layout design and selection often have notable effects on the performance of the manufacturing industry. This research investigates the Multi-Criteria Decision Making (MCDM) approach to find out the optimum plant layout design. The proposed methodology is demonstrated through the real-life setting for the gearbox manufacturing industry. Manual and computerized layout generation approach is used efficiently and accordingly, six layout designs are generated. The approach takes into account qualitative as well as quantitative performance criteria for the selection of layout design. Analytical Hierarchy Process (AHP) is applied to obtain the weight of qualitative measures. Ranking of alternatives is obtained through the application of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Weighted Aggregated Sum-Product Assessment (WASPAS) both integrated with the Entropy method. Empirical findings indicate that the rank acquired using the TOPSIS method is perfectly parallel to those acquired through the WASPAS method, which confirms the applicability and potential of these methods. Also, the effect of the parameter λ in WASPAS method on performance score is stable. At the same time, this paper analyses the rank reversal phenomenon and proves that the ranking proposed by TOPSIS satisfies ranking stability.
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