Optimization of end milling on Al–SiC-fly ash metal matrix composite using Topsis and fuzzy logic

Abstract

Metal matrix composites are extensively used in aerospace, automobile and other engineering applications as an alternative to a wide range of elements. High strength-weight ratio, durability and high corrosion resistance are benefits of metal matrix composites. The study that exhibits adopts optimal cutting parameters (speed, feed and depth of cut). The initial study is to explore end milling process of alumina (AA6082 with SiC 3% and fly ash 2%) molted metal matrix composite. The technique for order preference by similarity to ideal solution and fuzzy logic for optimizing the cutting parameter values has been utilized in the MMC. The response surface methodology is being used to develop the numerical model between output responses and machining parameters. The second-order regression models are studied through analysis of variance. The experimental investigation exhibits that feed rate is the important factor on response variables.

Investigation of the effect of vibration in the multi-objective optimization of dry turning of hardened steel

“…Apart from the implementation of parametric optimization of machining parameters during metal cutting, fuzzy TOPSIS was effective in various areas such as multi-response optimization of blended polymer composites (Şimşek and Uygunoğlu, 2016), optimization of drilling parameters for Al2O3 particles and sisal fiber-reinforced epoxy composites (Kamaraj et al ., 2018), optimization of the input parameters such as pulse on time, duty cycle, discharge current, etc. in the electron discharge machining process (Roy and Dutta, 2019) and optimization of the machining parameters of metal matrix composites (Al–SiC-fly ash) (Tamiloli et al ., 2019).…”

Interpolation and Milling Optimization of Titanium Alloy Based on Machine Learning and Multi-objective Algorithm

“…In the cutting tool length to diameter is large and complex curved surface parts processing, the conventional method of milling cutter are prone to deformation, able to withstand the radial cutting force is small, in order to avoid the flutter, affect the machining accuracy and other negative effect to adopt conservative cutting parameters, such as reducing cutting speed, cutting depth and cutting width, this limits the processing efficiency. In the process of interpolation and milling, the tool is fed along the spindle direction, and the rigidity of the cutting system is large, which can better avoid chatter, make the machining quality of parts more stable, and improve the cutting parameters appropriately to improve the material removal rate [14][15].…”

A novel MOALO-MODA ensemble approach for multi-objective optimization of machining parameters for metal matrix composites

“…Sidhu and Yazdani [11] employed desirability function and lexicographic goal programming to identify the optimal machining condition for having minimum residual stress, tool wear rate (TWR) and maximum material removal rate (MMR) during electrical discharge machining (EDM) of SiC/A359 MMC. Tamiloli et al [12] integrated fuzzy logic with technique for order of preference by similarity to ideal solution (TOPSIS) for optimization of the end milling parameters while machining Al-SiC-fly ash MMC. It was observed that feed rate, speed and depth of cut would significantly affect surface roughness and cutting force during the machining operation.…”