Application of Desirability Function Analysis and Utility Concept for Selection of Optimum Cutting Parameters in Turning Operation

2016 ◽  
Vol 15 (01) ◽  
pp. 1-11 ◽  
Author(s):  
B. Singaravel ◽  
T. Selvaraj
Keyword(s):  
Function Analysis ◽  
Removal Rate ◽  
Desirability Function ◽  
Cutting Parameters ◽  
Optimization Method ◽  
Relative Significance ◽  
Utility Concept ◽  
Coated Carbide ◽  
Desirability Function Analysis ◽  
Selection Of

Multi-objective optimization method is used to simultaneously maximize and minimize the various criteria involved in complex industrial problems. In the present work, the optimum combination of cutting parameters is estimated in the turning of EN25 steel with coated carbide tools by performing desirability function analysis and utility concept. The experiments were designed as per L18 Taguchi mixed level orthogonal array with each trial performed under different conditions. These methods are employed for minimization of cutting force, surface roughness and maximization of material removal rate. The optimized results are compared and utility concept gave good combination of input and output parameters. Finally, Analysis of Variance (ANOVA) on overall desirability and utility value was employed to identify the relative significance of factors in terms of their percentage contribution to the responses.

scholarly journals Machinability Studies and Optimization of AA 6082/Fly Ash/Carbonized Eggshell Matrix Composite

2021 ◽  
Vol 31 (4) ◽  
pp. 207-216
Author(s):  
Ndudim H. Ononiwu ◽  
Chigbogu G. Ozoegwu ◽  
Nkosinathi Madushele ◽  
Esther T. Akinlabi
Keyword(s):  
Fly Ash ◽  
Function Analysis ◽  
Removal Rate ◽  
Desirability Function ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Chip Morphology ◽  
Influential Factor ◽  
Depth Of Cut ◽  
Desirability Function Analysis

Machinability studies of aluminium matrix composites (AMCs) is a necessary investigation required to understand their behaviour during machining to produce components effectively and efficiently. This established need has led to the investigation into the machinability of AA 6082 reinforced with 2.5 wt.% fly ash and 2.5 wt.% carbonized eggshell fabricated via stir casting. The studied machinability indices were material removal rate (MRR), cutting temperature, built-up edges (BUE) formation and chip morphology while the selected inputs were cutting speed (100 mm/min, 200 mm/min, 300 mm/min), feed (0.1 mm/rev, 0.2 mm/rev, 0.3 mm/rev) and depth of cut (0.5 mm, 1 mm, 1.5 mm). For the experimental design, the L9 orthogonal array was preferred to create 9 experimental runs. The analysis of the built-up edges showed that it increased at lower cutting speeds and increased feed and depth of cut. The examination of the produced chips after each experimental run showed the presence of c-shaped, helically shaped and ribbon-shaped chips. The analysis of variance (ANOVA) for both MRR and cutting temperature indicated that the depth of cut was the most influential factor on both responses. Multi-objective optimization using desirability function analysis showed that the optimum combination of parameters was 300 mm/min, 0.2 mm/rev and 1.0 mm for the cutting speed, feed and depth of cut respectively. The ANOVA of the composite desirability indicated that the cutting speed was the most contributing factor.

Multi-Response Optimization in Turning of AA6061 T6 Using Desirability Function Analysis

2015 ◽  
Vol 812 ◽  
pp. 124-129 ◽  
Author(s):  
P. Jayaraman ◽  
L. Mahesh Kumar
Keyword(s):  
Function Analysis ◽  
Removal Rate ◽  
Desirability Function ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Multiple Responses ◽  
Ideal Approach ◽  
Response Optimization ◽  
Desirability Function Analysis

This paper presents an ideal approach for the optimization of machining parameters on turning of AA6061 T6 aluminium alloy with multiple responses based on orthogonal array with desirability function analysis. In this study, turning parameters namely cutting speed, feed rate and depth of cut are optimized with the considerations of multiple responses such as surface roughness (Ra), roundness (Ø) and material removal rate (MRR). Multi response optimization of machining parameters was done through desirability function analysis. The optimum machining parameters have been identified by a composite desirability value obtained from desirability function analysis. The performance index and significant contribution of process parameters were determined by analysis of variance.

Modelling and Optimization of End Milling Process Using TLBO and TOPSIS Algorithm

2017 ◽  
pp. 54-81 ◽  
Author(s):  
Atul Tiwari ◽  
Mohan Kumar Pradhan
Keyword(s):  
Material Removal Rate ◽  
Material Removal ◽  
Metal Cutting ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Optimization Method ◽  
Depth Of Cut ◽  
Multi Objective ◽  
Order Preference

To assure desire quality of machined products at minimum machining costs and maximum material removal rate, it is very important to select optimum parameters when metal cutting machine tool are used. Minimum Surface Roughness (Ra) is commonly desirable for the component; however Material Removal Rate (MRR) should be maximized. This chapter presents an approach for determination of the best cutting parameters precede to minimum Ra and maximum MRR simultaneously by integrating Response Surface Methodology with Multi-Objective Technique for Order Preference by Similarity to Ideal Solution and Teaching and learning based optimization algorithm in face milling of Al-6061 alloy. 30 experiments have been conducted based on RSM with 4 parameters, namely Speed, Feed, Depth of Cut and Coolant Speed and three levels each. ANOVA is performed to find the most influential input parameters for both MRR and Ra. Later the multi-objective attribution selection method TOPSIS and multi objective optimization method TLBO is used to optimize the responses.

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