scholarly journals Multi Response Optimization of Simultaneous Fixation of Reactive Printing and Crease Resistant Finishing Using Desirability Function

2013 ◽  
Vol 2 (6) ◽  
pp. 126-131
Author(s):  
Fareha Asim ◽  
Muzzaffar Mahmood
Keyword(s):  
Desirability Function ◽  
Response Optimization

Multi-criteria optimization and predictive modeling of turning forces in high-speed machining of yttria based zirconia toughened alumina insert using desirability function approach

2015 ◽  
Vol 231 (8) ◽  
pp. 1396-1408 ◽  
Author(s):  
Nilrudra Mandal ◽  
B Doloi ◽  
Biswanath Mondal ◽  
BK Singh
Keyword(s):  
Feed Rate ◽  
High Speed ◽  
Desirability Function ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Machining Forces ◽  
Feed Force ◽  
Response Optimization ◽  
Zirconia Toughened Alumina

An attempt has been made to apply the Taguchi parameter design method and multi-response optimization using desirability analysis for optimizing the cutting conditions (cutting speed, feed rate and depth of cut) on machining forces while finish turning of AISI 4340 steel using developed yttria based zirconia toughened alumina inserts. These zirconia toughened alumina inserts were prepared through wet chemical co-precipitation route followed by powder metallurgy process. The L9 (4) orthogonal array of the Taguchi experiment is selected for three major parameters, and based on the mean response and signal-to-noise ratio of measured machining forces, the optimal cutting condition arrived for feed force is A1, B1 and C3 (cutting speed: 150 m/min, depth of cut: 0.5 mm and feed rate: 0.28 mm/rev) and for thrust and cutting forces is A3, B1 and C1 (cutting speed: 350 m/min, depth of cut: 0.5 mm and feed rate: 0.18 mm/rev) considering the smaller-the-better approach. Multi-response optimization using desirability function has been applied to minimize each response, that is, machining forces, simultaneously by setting a goal of highest cutting speed and feed rate criteria. From this study, it can be concluded that the optimum parameters can be set at cutting speed of 350 m/min, depth of cut of 0.5 mm and feed rate of 0.25 mm/rev for minimizing the forces with 78% desirability level.

Experimental investigation of nanofluids in minimum quantity lubrication during turning of EN-24 steel

2019 ◽  
Vol 234 (5) ◽  
pp. 712-729
Author(s):  
Archana Thakur ◽  
Alakesh Manna ◽  
Sushant Samir
Keyword(s):  
Comparative Analysis ◽  
Desirability Function ◽  
Cutting Temperature ◽  
Minimum Quantity Lubrication ◽  
Hybrid Nanofluid ◽  
Machining Performance ◽  
Optimization Of Parameters ◽  
Minimum Quantity ◽  
Response Optimization ◽  
Hybrid Nanofluids

The present work evaluates the performance of different machining environments such as dry, wet, minimum quantity lubrication, Al2O3 nanofluids based minimum quantity lubrication, CuO nanofluids based minimum quantity lubrication and Al–CuO hybrid nanofluids based minimum quantity lubrication on machining performance characteristics during turning of EN-24. The nanofluids and hybrid nanofluids were prepared by adding the Al2O3, CuO and Al2O3/CuO to the soluble oil with different weight percentages (0.5 wt.%, 1 wt.%, 1.5 wt.%). The thermal and tribological properties of hybrid nanofluid and nanofluids were analyzed. The comparative analysis of different turning environments has been done. From comparative analysis it is clearly observed that the nanofluids and hybrid nanofluid shows better performance during turning of EN-24 steel. So there is a need for optimization of parameters during turning of EN-24 under Al2O3 nanofluids based minimum quantity lubrication, CuO nanofluids based minimum quantity lubrication and Al–CuO hybrid nanofluids based minimum quantity lubrication. The optimization of parameters has been done by response surface methodology. The significance of developed model was identified from analysis of variance. Multi-response optimization was done using desirability function approach. To verify the accuracy of developed models, confirmatory experiments were performed. The experimental results reveal that Al–CuO hybrid nanofluids based minimum quantity lubrication significantly improves surface quality, reduces cutting temperature and cutting forces.

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