Please use this identifier to cite or link to this item: http://dspace.dtu.ac.in:8080/jspui/handle/repository/18024
Title: OPTIMIZATION OF RESPONSE VARIABLE OF NATURAL FIBER REINFORCRED EPOXY COMPOSITE AND DELRIN
Authors: KANWAR, SUSHEEM
Keywords: NATURAL FIBER
COMPOSITE
GENETIC ALGORITHM
ANALYSIS OF VARIANCE
RESPONCE SURFACE METHODOLOGY
Issue Date: Jul-2020
Series/Report no.: TD-4890;
Abstract: Climate change has necessitated the development of “green” alternatives to replace existing materials. This focus has resulted in the push towards fabricating natural fiber reinforced polymer composites. This research work looks at rice husk ash and groundnut shell ash reinforced epoxy composites as well as the polymer Delrin which are promising alternatives to metal composites for a wide variety of applications. Wear test on the epoxy composites was done using ball on flat tribometer under room temperature. A 6mm steel ball was used as a counter body and 4 different epoxy composite samples of 3cmx3cm were used as the flat. The 4 samples were: neat epoxy, epoxy reinforced with rice husk ash, epoxy which was reinforced using ash of groundnut shell and epoxy reinforced with both ash of rice husk as well as ash of groundnut shell. Upon carrying out the wear test it was found that neat epoxy composite had the maximum wear rate of 163 mm3 /Nm, whereas epoxy composite reinforced with both rice husk ash and groundnut shell ash was the most resistant to wear. Apart from wear test, the surface roughness of all the nine composite samples was measured and optimization through the implementation of genetic algorithm (GA) was done. It was found that a minimum surface roughness of 1.503μm can be obtained for an epoxy-hardener ratio of 2.99:1 and without the addition of any reinforcements. This optimization was achieved within 102 generations. Apart from GA, response surface methodology (RSM) and Taguchi design of experiments was carried out as well to optimize and the results obtained closely agreed with those obtained from GA. RSM gave an optimized surface roughness value of 1.39μm and the main effects plot showed that the best combination of input factor was a 3:1 ratio of epoxy to hardener with 0% reinforcement. Analysis of Variance (ANOVA) showed epoxy to hardener ratio as the most significant factor contributing 36.35% of the total effect. Similar to the epoxy composites, optimization of response variables through GA, RSM and Taguchi design of experiments was carried out for Delrin as well and the results compared. GA gave an optimized value of 0.351μm surface roughness and 1788.91mm3 /min material removal rate within 139 generations for a speed of 150rpm, feed of 0.6mm/rev and 1.49mm depth of cut. On the other hand, RSM gave an optimized value of 0.736μm surface roughness and 2436mm3 /min material removal rate for a speed of 192.42rpm, 0.458 mm/rev feed and 1.5mm depth of cut and Taguchi gave the best combination of input values as 150rpm speed, 0.6 mm/rev feed and 1.5mm depth of cut. These values closely agreed with that of GA. ANOVA showed depth of cut was the most significant factor contributing 57.72% of the total effect.
URI: http://dspace.dtu.ac.in:8080/jspui/handle/repository/18024
Appears in Collections:M.E./M.Tech. Production Engineering

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