Application of Desirability Approach to Determine Optimal Turning Parameters

2024-01-5022

02/20/2024

Features
Event
Automotive Technical Papers
Authors Abstract
Content
Aluminum alloys are employed in agricultural equipment, aerospace sectors, medical instruments, machinery, automobiles, etc. due to their physical and mechanical characteristics. The geometrical shape and size of the parts are modified in turning operation by using a single-point cutting tool. A356 aluminum alloy is widely used in various engineering sectors, hence there is a necessity to produce A-356 components with quality. The inappropriate cutting parameters used in turning operation entail high production costs and reduce tool life. Box–Behnken design (BBD) based on response surface methodology (RSM) was used to design the experiments such that the experiment trials were conducted by varying cutting parameters like N-spindle speed (rpm), f-feed rate (mm/rev), and d-depth of cut (mm). The multi-objective responses, such as surface roughness (SR) and metal removal rate (MRR) were analyzed with the desirability method. The analysis of variance (ANOVA) represents the significant factor for each response, whereas the desirability approach focuses on a single optimal cutting parameter setting to achieve both responses with a better level of accuracy. The most favorable turning parameters N: 713.563 rpm (715 rpm), f: 1 mm/rev, and d: 1 mm was determined in the desirability approach to enhance results of SF: 2.511 μm and MRR 25.145 gm/min. The validation test was executed with predicted factors, such that the experiment results form a better agreement with the predicted results. The determined cutting parameters settings are advisable to machine the liquid metallurgical A-356 aluminum alloy castings.
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DOI
https://doi.org/10.4271/2024-01-5022
Pages
8
Citation
Arunbharathi, R., Arish, R., Girith Chandru, S., Bhavandharshan, K. et al., "Application of Desirability Approach to Determine Optimal Turning Parameters," SAE Technical Paper 2024-01-5022, 2024, https://doi.org/10.4271/2024-01-5022.
Additional Details
Publisher
Published
Feb 20
Product Code
2024-01-5022
Content Type
Technical Paper
Language
English