Title:

Optimum combination of machining parameters during drilling of Aluminium 7075 alloys using Grey based Taguchi approach

Creator:

Reddy Sreenivasulu ; Ch. Srinivasa Rao

Subject:

drilling ; burr size ; surface roughness ; roundness error ; thrust force ; torque ; taguchi method ; grey relational analysis

Description:

From ancient days to till today manufacturing industries, especially making of holes on the parts during drilling process for precision assembling of parts facing problems with burr formation. Drilling operation is one of the finishing operation in the production cycle, removing of burrs during drilling process is a time consuming and non-value added process to the manufacturing sector. So reducing the size of burrs is the main aim of the present study. In the present work, optimization of burr size is considered during drilling of aluminium 7075 alloy. From Grey relational grades of responses selected optimal combination of parameters to attain multiple performance characteristics of responses with a corresponding higher grey relational grade. For identifying the most significant input parameters that influence the output responses ANOVA is conducted. Finally, observations reveals that feed rate, point and clearance angles are the most influential factors on burr size and also experimental results divulge that the lower the thrust force causes to decrease the burr height. The proposed approach is helpful to the budding entrepreneurs in the related areas to select optimal combination of drilling parameters to attain multiple performance characteristics of responses especially in burr size to prevent the post finishing operations.

Place of publishing:

Koszalin

Publisher:

Publishing House of the Koszalin University of Technology

Date:

2020

Type:

artykuł w czasopiśmie

Format:

application/pdf

Language:

eng

Is part of:

Journal of Mechanical and Energy Engineering. Vol.4 (44), nr 3, s. 227-238

Rights:

Biblioteka Politechniki Koszalińskiej

Access rights:

internet

License:

Creative Commons BY 4.0