Optimization of Reaming Process Parameters for Titanium Ti-6Al-4V Alloy Using Grey Relational Analysis

2016 ◽  
Author(s):  
Shakeel Ahmed L. ◽  
Pradeep Kumar M.
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Research Work ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Factors Affecting ◽  
Significant Control ◽  
Relational Analysis ◽  
Control Factors ◽  
Grey Relational

Reaming is one of the finishing processes that have been widely applied in manufacturing industries. Reaming of Titanium Ti-6Al-4V alloy material is an important and current research topic on manufacturing processes. Optimal process parameter setting is an important element in the machinability study of Titanium Ti-6Al-4V alloy. Optimization has most significant importance, particularly for reaming operations. This research work focuses on the multi-response optimization of reaming process parameters using the Taguchi and Grey relational technique to obtain minimum cutting temperature (T), thrust force (Ft), torque (Mt), surface roughness (Ra) and hole quality. The experiments were performed on Titanium Ti-6Al-4V alloy using uncoated carbide straight shank reamer under wet and cryogenic LN2 conditions. Eighteen experimental runs (L18) based on the Taguchi method of orthogonal arrays were performed to determine the best factor level condition. The environment, cutting speed and feed rate were selected as control factors. Grey relational analysis was used to determine the most significant control factors affecting the output parameters. Grey relational grade obtained from the grey relational analysis was used to solve the reaming process with the optimal levels of the multiple performance characteristics responses were established. The optimum results indicate that the reaming results have been improved in wet coolant than the cryogenic LN2 condition.

Analysis and Optimization of Wire EDM Process of Titanium by Using GRA Methodology

2019 ◽  
Vol 969 ◽  
pp. 678-684 ◽  
Author(s):  
Sarat Kumar Sahoo ◽  
A. Bara ◽  
A.K. Sahu ◽  
S.S. Mahapatra ◽  
D.S. Kiran ◽  
...  
Keyword(s):  
Grey Relational Analysis ◽  
Orthogonal Array ◽  
Electrical Discharge Machining ◽  
Input Parameter ◽  
Optimization Technique ◽  
Research Work ◽  
Cutting Speed ◽  
Machining Process ◽  
Relational Analysis ◽  
Grey Relational

In this research work, an efficient optimization technique, grey relational analysis (GRA) has been used to for optimization of wire electrical discharge machining process of Titanium (grade 2) by considering multiple output parameters. This technique combines Taguchi’s orthogonal array with grey relational analysis for the design of the experiment. The central focus of this research is to achieve improved Kerf width, surface roughness and cutting speed. GRA method is implemented to decide the best input parameter that optimizes the output parameters. This study has been conducted by applying Taguchi’s L9 orthogonal array. Each experiment has been conducted in altered conditions of input variables. For the optimization of multiple criteria, GRA is suggested as a suitable technique for the optimization of complex interrelationships between multi-performance characteristics. By analysis of variance (ANOVA) it is found that the percentage of contribution of peak current on overall performance is maximum i.e.73.1%.

Optimization of Multiple Responses in Dry Turning Process Using Taguchi-Grey Relational Analysis

2014 ◽  
Vol 592-594 ◽  
pp. 620-624
Author(s):  
Sumit Verma ◽  
Hari Singh
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Tangential Force ◽  
Cutting Speed ◽  
Relational Theory ◽  
Depth Of Cut ◽  
Multiple Responses ◽  
Relational Analysis ◽  
Grey Relational ◽  
Optimal Cutting Parameters

The present study investigates the optimization of multiple responses in turning of EN-8 steel by the Taguchi and grey relational analysis. The performance characteristics considered are tangential force, feed force and radial force. Grey relational theory is adopted to determine the best process parameters that give lower magnitude of tangential, feed, radial forces and optimal cutting parameters. An orthogonal array L18 is used for the experimental design. The setting of process parameters— nose radius, 0.8mm; cutting speed, 60.65 m/min; feed rate, 0.04 mm/rev; and depth of cut, 0.60 mm— has highest grey relational grade and therefore produces best turning performance in terms of cutting forces.

scholarly journals Parameter Optimisation in Vibration Assisted Turning of Ti6Al4V Alloy using ANOVA and Grey Relational Analysis

2018 ◽  
Vol 15 (3) ◽  
pp. 5400-5420 ◽  
Author(s):  
D. Venkata Sivareddy ◽  
P. Vamsi Krishna ◽  
A. Venu Gopal ◽  
C. L. Prithvi Raz
Keyword(s):  
Optimum Condition ◽  
Cutting Force ◽  
Grey Relational Analysis ◽  
Feed Rate ◽  
Equivalent Stress ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Ti6al4v Alloy ◽  
Relational Analysis ◽  
Grey Relational

The machining of Ti6Al4V alloy with vibration assisted turning (VAT) is an effective consideration to control the surface integrity of machined components. The effect of cutting and vibrating parameters in a VAT on cutting force, cutting temperature, equivalent stress and compressive maximum circumferential residual stress (MCRS) was studied in the present work. The parameter optimisation of a VAT of Ti6Al4V alloy was achieved with Taguchi based analysis of variance (ANOVA) and grey relational analysis (GRA). The input parameters considered for optimisation of VAT process are cutting speed, feed rate, frequency and amplitude. The finite element (FE) simulations were performed with commercial FE code, ABAQUS. The result shows that the vibrating parameters (frequency and amplitude) play a significant role than cutting parameters (speed and feed rate) in VAT process. The optimum condition for each output response was determined from ANOVA. The optimum condition obtained at 30 m/min of cutting speed, 150 μm of amplitude, 600 Hz of frequency and 0.05 mm/rev of feed rate for cutting force, cutting temperature and MCRS (compressive) while the optimum condition for equivalent stress is 30 m/min of cutting speed, 100 μm of amplitude, 600 Hz of frequency and 0.05 mm/rev of feed rate. The GRA suggests the combination of process parameters 30 m/min of cutting speed, 150 μm of amplitude, 600 Hz of frequency and 0.05 mm/rev of feed rate provides the optimum response.

scholarly journals Analysis and optimization of laser drilling process during machining of AISI 303 material using grey relational analysis approach

2021 ◽  
Vol 3 (3) ◽  
Author(s):  
V. Chengal Reddy ◽  
Thota Keerthi ◽  
T. Nishkala ◽  
G. Maruthi Prasad Yadav
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Pulse Frequency ◽  
Laser Drilling ◽  
Simultaneous Optimization ◽  
Fibre Laser ◽  
Drilling Process ◽  
Relational Analysis ◽  
Grey Relational

AbstractSurface roughness and heat-affected zone (HAZ) are the important features which influence the performance of the laser-drilled products. Understanding the influence of laser process parameters on these responses and identifying the cutting conditions for simultaneous optimization of these responses are a primary requirement in order to improve the laser drilling performance. Nevertheless, no such contribution has been made in the literature during laser drilling of AISI 303 material. The aim of the present work is to optimize the surface roughness (Ra) and HAZ in fibre laser drilling of AISI 303 material using Taguchi-based grey relational analysis (GRA). From the GRA methodology, the recommended optimum combination of process parameters is flushing pressure at 30 Pa, laser power at 2000 W and pulse frequency at 1500 Hz for simultaneous optimization of Ra and HAZ, respectively. From analysis of variance, the pulse frequency is identified as the most influenced process parameters on laser drilling process performance.

scholarly journals Multi-Response Optimization of Coagulation and Flocculation of Olive Mill Wastewater: Statistical Approach

2021 ◽  
Vol 11 (5) ◽  
pp. 2344
Author(s):  
Srikanth Vuppala ◽  
Riyaaz Uddien Shaik ◽  
Marco Stoller
Keyword(s):  
Grey Relational Analysis ◽  
Research Work ◽  
Olive Mill Wastewater ◽  
Relational Analysis ◽  
Coagulation And Flocculation ◽  
Coagulant Dosage ◽  
Response Optimization ◽  
Grey Relational ◽  
Flocculation Process ◽  
Olive Mill

Olive oil production is one of the important industrial sectors within the agro-food framework of the Mediterranean region, economically important to the people working in this sector, although there is also a threat to the environment due to residues. The main wastes of the olive oil extraction process are olive mill wastewater (OMW) and olive husks which also require proper treatment before dismissal. In this research work, the main goal is to introduce grey relational analysis, a technique for multi-response optimization, to the coagulation and flocculation process of OMW to select the optimum coagulant dosage. The coagulation and flocculation process was carried out by adding aluminum sulfate (Alum) to the waste stream in different dosages, starting from 100 to 2000 mg/L. In previous research work, optimization of this process on OMW was briefly discussed, but there is no literature available that reports the optimal coagulant dosage verified through the grey relational analysis method; therefore, this method was applied for selecting the best operating conditions for lowering a combination of multi-responses such as chemical oxygen demand (COD), total organic carbon (TOC), total phenols and turbidity. From the analysis, the 600 mg/L coagulant dosage appears to be top ranked, which obtained a higher grey relational grade. The implementation of statistical techniques in OMW treatment can enhance the efficiency of this process, which in turn supports the preparation of waste streams for further purification processes in a sustainable way.

Sign in / Sign up

Export Citation Format

Share Document