Application of Taguchi based Grey Method for Multi Aspects Optimization on CNC Turning of AlSi7 Mg

Prakash, Prem; Raju, K.; Subbaiah, K. Venkata; Krishnamachary, P. C.; Manikandan, N.; Ramya, V.

doi:10.1016/j.matpr.2018.03.011

Cited by 10 publications

(2 citation statements)

References 12 publications

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“…Smaller the better option: response across all runs, respectively. The distinguishing coe cient δ is a parameter that ranges from 0 to 1, with a common choice being 0.5 for balancing the comparability and distinguishability of the parameters [42,43]. By computing the GRC, the signi cance of each process parameter can be evaluated, aiding in the optimization of laser cladding conditions for Stelcar powder coatings on AZ61 magnesium alloy.…”

Section: Grey Relational Analysis (Gra) Of Mechanical Responsesmentioning

confidence: 99%

Parameter Optimization of Laser Cladding for Stelcar Powder Coatings on AZ61 Magnesium Alloy

et al. 2024

Preprint

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The main objective of this study is to improve the surface coating characteristics and reduce the dilution rate of AZ61 magnesium alloy using the laser cladding technique. This research work employed Taguchi (L16) orthogonal experimental design to investigate the relationship between process parameters and a cladding quality index. Parameters such as Scanning Speed (SS), Laser Power (LP), Powder Feed Rate (PFR) and Gas Flow (GF) were varied to analyze their impact on wear volume, dilution rate and micro-hardness of the key response variables in the laser cladding setup. Signal-to-noise ratios were calculated for each parameter to identify their individual effects on the responses. The findings indicated that powder feed rate predominantly influenced wear volume, accounting for 88.18% of its variation, while scanning speed has the highest influence on dilution rate (73.20%), and laser power significantly affected micro-hardness (84.60%). This study utilized grey relational analysis to determine the optimum processing parameters which simultaneously reduced wear volume, minimized dilution rate and enhanced micro-hardness. In particular, inclusion of Stelcar alloy powder in the substrate significantly influenced these outcomes. The application of grey relational analysis allowed the researchers to integrate multiple optimization objectives into a strategy, resulting in a clad with superior micro-hardness and minimal wear volume and dilution rate. The optimized parameters achieved the desired goals with a high degree of accuracy, confirming the effectiveness of multi-objective optimization in enhancing coating qualities and controlling dilution rate through laser cladding.

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Section: Grey Relational Analysis (Gra) Of Mechanical Responsesmentioning

confidence: 99%

Parameter Optimization of Laser Cladding for Stelcar Powder Coatings on AZ61 Magnesium Alloy

et al. 2024

Preprint

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“…Based on Taguchi's experimental design plan, Bilga et al [17] Akkuş [24] considered cutting speed, feed rate and depth of cut as the process parameters in CNC machining of AISI 1040 steel material, and identified their optimal settings for having minimum SR values. Bhanu Prakash et al [25] treated spindle speed, feed rate and depth of cut as the input parameters, and MRR and SR as the responses during CNC turning operation of AlSi 7 Mg material.…”

Section: Literature Surveymentioning

confidence: 99%

Decision Tree-based Parametric Analysis of a CNC Turning Process

Chakraborty¹,

Dandge²

2020

Scientia Iranica

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Computer numerical control (CNC) is a manufacturing concept where machine tools are automated to perform some predefined functions based on the instructions fed to them. CNC turning processes have found wide ranging applications in modern day manufacturing industries due to their capabilities to produce low cost high quality parts/components with very close dimensional tolerances. In order to exploit the fullest potential of a CNC turning process, it should always be operated while setting its different input parameters at their optimal levels. In this paper, two classification tree algorithms, i.e. classification and regression tree (CART) and Chi-squared automatic interaction detection (CHAID) are applied to study the effects of various turning parameters on the responses and identify the best machining conditions for a CNC process. It is perceived that the obtained settings almost match with the observations of the earlier researchers. The CART algorithm outperforms CHAID with respect to higher overall classification accuracy and lower prediction risk.

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Multi-objective optimization of coating properties and cladding efficiency in 316L/WC composite laser cladding based on grey relational analysis

Lian

Xiao

Zhang

et al. 2021

Int J Adv Manuf Technol

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Application of Taguchi based Grey Method for Multi Aspects Optimization on CNC Turning of AlSi7 Mg

Cited by 10 publications

References 12 publications

Parameter Optimization of Laser Cladding for Stelcar Powder Coatings on AZ61 Magnesium Alloy

Parameter Optimization of Laser Cladding for Stelcar Powder Coatings on AZ61 Magnesium Alloy

Decision Tree-based Parametric Analysis of a CNC Turning Process

Multi-objective optimization of coating properties and cladding efficiency in 316L/WC composite laser cladding based on grey relational analysis

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