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Application of Taguchi Technique for Optimization of Drilling Parameters and Analysis of Variance (ANOVA) for Drilling of Aluminium Alloy Al7068

Amardeepak M.*, Narayan B. Doddapattar**, Sanjeeva Murthy ***

*-** Cambridge Institute of Technology (North Campus), Bengaluru, Karnataka, India.

*** Department of Mechanical Engineering, Sri Siddhartha Institute of Technology, Tumkur, Karnataka, India.

Periodicity:February - April'2020
DOI : https://doi.org/10.26634/jme.10.2.16930

Abstract

Aluminium alloys offer good mechanical properties and are lightweight. The most widely used non-ferrous metals in engineering are aluminium and its alloys, and are widely used in the automotive and aerospace industries. Aluminium alloys as a class are considered as the family of materials offering the highest levels of machinability, as compared to other families of lightweight metals such as titanium and magnesium alloys. This machinability quantifies the machining performance and may be defined for a specific application by various criteria, such as tool life, surface finish, chip evacuation, material removal rate, and machine-tool power. Some of the methods employed for optimization of process parameters are Taguchi method, ANOVA, Genetic Algorithm (GA), Grey Relational Analysis (GRA), Particle Swarm Optimization (PSO), and Artificial Neural Network (ANN). The present work mainly focuses on optimization of process parameters for drilling of aluminium alloy Al7068 by varying the composition of one of the major elements, Mg in the alloy. Drilling of Al7068 alloy was carried out in the drill machining centre Hartford Pro-1000 with the experiments conducted based on Taguchi's L16 Orthogonal Array to get the optimized values of the drilling parameters. The coolant Quaker cool 7101 AFH had been used for drilling operation. The drilling parameters selected were feed, speed, depth of cut, drill bit diameter, and material composition varied in 4 levels. The ANOVA plots were studied to determine the influence of the process parameters (drilling parameters) on machining responses, such as surface roughness, material removal rate, machining time, machining force, and machining power. The results from ANOVA analysis indicate that feed rate highly impacts on the surface roughness, speed on material removal rate, material composition on machining time, machining force, and machining power.

Keywords

Aluminium Alloy, Magnesium, Zinc, Drilling Parameters, Material Composition (MC), Taguchi Method, ANOVA.

How to Cite this Article?

Amardeepak, M., Doddapattar, N. B., and Murthy, S. (2020). Application of Taguchi Technique for Optimization of Drilling Parameters and Analysis of Variance (ANOVA) for Drilling of Aluminium Alloy Al7068. i-manager’s Journal on Mechanical Engineering, 10(2), 11-17. https://doi.org/10.26634/jme.10.2.16930

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