Multi objective optimization of waste abrasive waterjet on mechanical properties of heat-treated A356 using Greytaguchi method

Stivensone, Valenteno (2022) Multi objective optimization of waste abrasive waterjet on mechanical properties of heat-treated A356 using Greytaguchi method. Project Report. Melaka, Malaysia, Universiti Teknikal Malaysia Melaka. (Submitted)

	Text (24 Pages) Multi objective optimization of waste abrasive waterjet on mechanical properties of heat-treated A356 using Greytaguchi method.pdf - Submitted Version Download (461kB)
	Text (Full Text) Multi objective optimization of waste abrasive waterjet on mechanical properties of heat-treated A356 using Greytaguchi method.pdf - Submitted Version Restricted to Registered users only Download (2MB)

Abstract

Greensand casting is still widely used in the manufacturing industry because of its low production costs and ease of processing complicated products. The setup of the casting process is critical for achieving quality and efficiency. However, the price of silica sand has doubled in comparison to the typical price in today’s market. Therefore, this study aims to optimize the waste abrasive waterjet parameters (bentonite, coal dust, water) of T6 heat treatment A356 Aluminium alloy using Taguchi based grey relational analysis. Design of Experiment (DOE) was used to plan the parameter of green sand ingredients with waterjet using Grey relational Analysis Method (GRA). The casting and T6 heat treatment process was carried out. After solidification, the A356 Aluminium alloy was tested for tensile strength, hardness, and microstructure. After that, the Grey-Taguchi method was used to analyse the data of mechanical of optimum composition for T6 heattreated A356 samples acquired from the tests. In addition, an analysis of variance (ANOVA) table summarised the findings. According to the Grey-Taguchi analysis, the ideal green sand composition in tensile and hardness tests is 60% Silica sand and 40% garnet sand, whereas Bentonite, Water, and Coal Dust will be the following the determined parameters. Sample 9 has the highest tensile and hardness value, whereas Sample 1 has the lowest value. In tensile tests, the best green sand composition is 12% Bentonite, 5% Coal Dust, and 6% Water, whereas in hardness tests, the best green sand composition is 9% Bentonite, 6% Coal Dust, and 7% Water. The best green sand composition, as per Grey Relational Grade (GRG) analysis, is 12% Bentonite, 6% Coal Dust, and 6% Water. Based on the ANOVA table, there is a statistically significant relationship between SN ratios and bentonite in the tensile test, however, in the hardness test, there is a statistically significant relationship between SN ratios and coal dust. Finally, with the magnification of an Upright Light microscope, the microstructure of Sample 9 has the highest while Sample 1 has the lowest silicon boundaries region.

Actions (login required)

View Item