scholarly journals Optimization of multiple quality characteristics for end milling under dry cutting environment using desirability function

2021 ◽  
Vol 2070 (1) ◽  
pp. 012218
Author(s):  
V V N Sarath ◽  
N Tamiloli
Keyword(s):  
Surface Roughness ◽  
Aluminum Alloy ◽  
End Milling ◽  
Function Analysis ◽  
Desirability Function ◽  
Substantial Contribution ◽  
Machining Parameters ◽  
Characteristic Analysis ◽  
Dry Cutting ◽  
Desirability Function Analysis

Abstract Milling AA6082T6 materials is a difficult venture because of their heterogeneity and a slew of problems, inclusive of surface roughness, that get up for the duration of the machining method and are connected to the material’s homes and slicing settings. The optimization of machining parameters is a crucial section inside the manufacturing method. This research introduces a unique approach for improving machining settings whilst milling aluminum alloy. A technique notorious as desirability function analysis (DFA) turned into worn to optimize machining parameters. DFA is a effective tool for optimizing multi-reaction problems. Milling research for aluminum alloy were completed using tungsten carbide end milling inserts in dry situations, based totally on Taguchi’s L9 orthogonal array. Multi-response issues, along with machining pressure and surface roughness, are used to optimize machining parameters including feed charge, spindle speed, and depth of reduce. person desirability values from the desirability characteristic analysis are used to create a composite desirability cost for the multi-responses. The most effective ranges of parameters had been discovered based at the composite desirability fee and substantial contribution of parameters has been determined the usage of analysis of variance.

Optimization in Hot Turning of Nickel Based Alloy Using Desirability Function Analysis

2016 ◽  
Vol 24 ◽  
pp. 64-70 ◽  
Author(s):  
A.K. Parida ◽  
K.P. Maity
Keyword(s):  
Feed Rate ◽  
Function Analysis ◽  
Desirability Function ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Cutting Velocity ◽  
Nickel Based Alloy ◽  
Desirability Function Analysis ◽  
Hot Turning

This paper presents a desirability function approach in order to find out an optimal combination of Machining parameters for multi-response parameters in hot turning operation of nickel based alloy. Taguchi’s L9 orthogonal array is used for experimental design. The machining parameters such as cutting velocity, feed rate, depth of cut and temperature are optimized by multi-response considerations namely power, flank wear, and MRR. ANOVA test was carried out and it was found that cutting speed is most influence parameter followed by feed rate, depth of cut and workpiece temperature. The optimization of machining parameters was found at 5.8 m/min of cutting speed, 30 °C preheating temperature, 0.2 mm depth of cut and 0.15 mm/rev feed rate

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.

scholarly journals Desirability Function Analysis (DFA) in Multiple Responses Optimization of Abrasive Water Jet Cutting Process

2022 ◽  
Vol 3 (1) ◽  
pp. 11-19
Author(s):  
Andrzej Perec ◽  
Keyword(s):  
Surface Roughness ◽  
Function Analysis ◽  
Desirability Function ◽  
Traverse Speed ◽  
Abrasive Water Jet ◽  
Control Parameters ◽  
Cutting Depth ◽  
Water Jet Cutting ◽  
Abrasive Water Jet Cutting ◽  
Desirability Function Analysis

This paper introduces optimization of machining parameters for high-pressure abrasive water jet cutting of Hardox 500 steel utilizing desirability function analysis (DFA). The tests were carried out according to the orthogonal matrix (Taguchi) L9. The control parameters of the process such as pressure, abrasive flow rate, and traverse speed was optimized under multi-response conditions namely cutting depth and surface roughness. The optimal set of control parameters was established on the basis of the composite desirability value obtained from desirability function analysis and the significance of these parameters was determined by analysis of variance (ANOVA). The effects show that optimal sets for high cutting depth and small surface roughness is high pressure, middle abrasive flow rate, and small traverse speed. A confirmation test was also leaded to validate the test results. Results of the research have shown that machining efficiency at keeping good level quality of cut surface can be improved this approach.

Statistical Approach to Modeling & Optimization of Surface Roughness in High Speed End Milling of Silicon with Diamond Coated Tools

2012 ◽  
Vol 576 ◽  
pp. 28-31 ◽  
Author(s):  
A.K.M. Nurul Amin ◽  
Noor Syairah Khalid ◽  
Siti Nurshahida Mohd Nasir ◽  
Muammer D. Arif
Keyword(s):  
Surface Roughness ◽  
Response Surface ◽  
High Speed ◽  
End Milling ◽  
Desirability Function ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Coated Tools ◽  
Milling Machines ◽  
Air Blowing

This research demonstrated the use of conventional milling machines with diamond coated tools, high speed attachments, and air blowing mechanisms for ductile mode machining of silicon and subsequently modeling and optimizing the resultant surface roughness. Spindle speed, depth of cut, and feed rate, ranges: 60,000 to 80,000 rpm, 10 to 20 µm, and 5 to 15 mm/min respectively, were considered as the independent machining parameters for the modeling process. Compressed air at 0.35 MPa was also provided to prevent chip deposition on the finished surfaces. The resultant surfaces were analysed using Optical and Scanning Electron (SEM) Microscopes as well as Wyko NT 1100 and SurfTest SV-500 profilometers. The response, surface roughness, was then modeled using a small Central Composite Design (CCD) in Response Surface Methodology (RSM). The quadratic relation was found to be most suitable following Fit and Summary and ANOVA analyses. The relation was then optimized using Desirability Function (DF) in Design of Expert (DOE) software. The optimum attainable surface roughness, which was validated using experimental runs, was found to be 0.11 µm which may be considered quite satisfactory.

Improvement of CNC Lathe Performances by Tungsten-Carbide Tool Using Desirability Function Analysis for Fabrication of Miniature Component

2020 ◽  
Vol 1002 ◽  
pp. 3-11
Author(s):  
Azzam Sabah Hameed ◽  
Mohaned S. Jafar ◽  
Bijan Mallick
Keyword(s):  
Surface Roughness ◽  
Wear Rate ◽  
Tool Wear ◽  
Function Analysis ◽  
Desirability Function ◽  
Depth Of Cut ◽  
Tool Wear Rate ◽  
Cnc Lathe ◽  
Tungsten Carbide Tool ◽  
Desirability Function Analysis

Computer numerical control (CNC) machine has greater utility in the modern advanced industrial field. This paper deals with the parametric effects such as spindle speed (1500-2100 rpm) (N) (X1), depth of cut (DOC) (0.15-0.55 mm) (X2) and feed rate (f) (30-50 mm/min) (X3) on machining characteristics like tool wear rate (TWR) and surface roughness (Ra) during fabrication of IS-617 Aluminum miniature component by advanced CNC lathe using Tungsten-carbide tool. The article analyzes the second-order mathematical model development with co-relation of co-efficient of regression (COR) and analysis of variances (ANOVA) using desirability function analysis during the production of the miniature segment. The paper also consists of multi-criteria optimization for achieving the optimal parametric combination for minimum surface roughness and tool wear rate for this manufacturing operation. The paper also shows the fabricated micro-product of Aluminum at the optimal parametric conditions using CNC programming. It is found that spindle speed has a greater effect on the tool wear rate and depth of cut has dominating effects on surface roughness of job specimen. Desirability parametric combination for minimized surface roughness as well as tool wear rate has been found 1523 rpm/0.15mm/30mmmin-1.

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