Optimization of Process Parameters Using Soft Computing Techniques

2017 ◽  
pp. 177-220
Author(s):  
Supriyo Roy ◽  
Kaushik Kumar ◽  
J. Paulo Davim
Keyword(s):  
Soft Computing ◽  
Process Parameters ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Principal Component ◽  
Optimization Of Process Parameters ◽  
Hard Metals ◽  
Optimal Values ◽  
Grey Relational ◽  
Conventional Machining

Machining of hard metals and alloys using Conventional machining involves increased demand of time, energy and cost. It causes tool wear resulting in loss of quality of the product. Non-conventional machining, on the other hand produces product with minimum time and at desired level of accuracy. In the present study, EN19 steel was machined using CNC Wire Electrical discharge machining with pre-defined process parameters. Material Removal Rate and Surface roughness were considered as responses for this study. The present optimization problem is single and as well as multi-response. Considering the complexities of this present problem, experimental data were generated and the results were analyzed by using Taguchi, Grey Relational Analysis and Weighted Principal Component Analysis under soft computing approach. Responses variances with the variation of process parameters were thoroughly studied and analyzed; also ‘best optimal values' were identified. The result shows an improvement in responses from mean to optimal values of process parameters.

Process Optimization in Non-Conventional Processes

2017 ◽  
pp. 82-119
Author(s):  
Milan Kumar Das ◽  
Tapan Kumar Barman ◽  
Prasanta Sahoo ◽  
Kaushik Kumar
Keyword(s):  
Process Parameters ◽  
Morphological Study ◽  
Artificial Bee Colony ◽  
Removal Rate ◽  
Work Piece ◽  
Bee Colony ◽  
Hard Metals ◽  
Optimal Values ◽  
Grey Relational ◽  
Conventional Machining

Conventional machining becomes non-efficient and non-effective in case of intricate shape and also while working with hard metals and alloys due to excessive tool wear. In such situations non-conventional machining, in contrast becomes more appropriate due to non-contact between tool and work-piece. In the present study, EN31 steel was machined using Plasma Arc Cutting with pre-defined process parameters. Material Removal Rate and Surface roughness were considered as responses for the study. The responses were optimized both as single and multi-response. Considering the complexities of this present problem, experimental data were generated and the results were analyzed by using Taguchi, Grey Relational Analysis and Artificial Bee Colony (ABC) Algorithm. Responses variances with the variation of process parameters were thoroughly studied and analyzed and ‘best optimal values' were identified. The result were verified by the morphological study. It was observed that there was an improvement in responses from mean to optimal values of process parameters.

Evaluation of Optimal Parameters for Machining Aluminium Alloy Al6061 in Wire EDM

2014 ◽  
Vol 592-594 ◽  
pp. 282-288
Author(s):  
T. Bharathy ◽  
K. Thiruppathi ◽  
S. Raghuraman
Keyword(s):  
Aluminium Alloy ◽  
Process Parameters ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Objective Measure ◽  
Wire Edm ◽  
Machined Surface ◽  
Optimization Of Process Parameters ◽  
Grey Relational Grade ◽  
Grey Relational

This paper discuss on the optimization of process parameters for the machining of Al6061 aluminium alloy in Wire Electrical Discharge Machining (WEDM). Al6061 has a significant use in various domains like aerospace, ordnance, and automotive sectors. Wire EDM is used in the fields of Dies, Moulds Precision Manufacturing and contour cutting. The experiments have been conducted by varying four process parameters such as Peak current, Ton, Toffand Servo feed in three different levels. The important output measurable parameters like material removal rate (MRR), Surface roughness (Ra) value of the machined surface for each experimental runs has been measured. Taguchi’s L9(34) Orthogonal Array was employed to carry on the experiments, that agree with arbitrarily opted distinct combinations of the mentioned process parameter. All experiments have been conducted using Electronica Sprintcut WEDM. Grey relational analysis was employed to change over the multi-objective measure into a tantamount individual objective function. Taguchi technique was used to optimize the overall grey relational grade. Verification experiments were done to validate the optimal results.

Multi-Objective Optimization of EDM Process Parameters using Taguchi Method, Principal Component Analysis and Grey Relational Analysis

2014 ◽  
Vol 4 (2) ◽  
pp. 29-46 ◽  
Author(s):  
U. Shrinivas Balraj ◽  
A. Gopala Krishna
Keyword(s):  
Principal Component Analysis ◽  
Taguchi Method ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Electrical Discharge Machining ◽  
Principal Component ◽  
Component Analysis ◽  
Optimum Process ◽  
Relational Analysis ◽  
Grey Relational

This paper investigates multi-objective optimization of electrical discharge machining process parameters using a new combination of Taguchi method and principal component analysis based grey relational analysis. In this study, three conflicting performance characteristics related to surface integrity such as surface roughness, white layer thickness and surface crack density are considered in electrical discharge machining of RENE80 nickel super alloy. The process parameters considered are peak current, pulse on time and pulse off time. The experiments are conducted based on Taguchi method and these experimental results are used in grey relational analysis and weights of the corresponding performance characteristics are determined by principal component analysis. The weighted grey relational grade is used as a performance index to determine optimum process parameters and results of the confirmation experiments indicate that the combined approach is effective in determining optimum process parameters.

Optimization of Process Parameters for Silicon Carbide Powder Mixed EDM

2019 ◽  
pp. 55-81
Author(s):  
Sasmeeta Tripathy ◽  
Deba Kumar Tripathy
Keyword(s):  
Process Parameters ◽  
Removal Rate ◽  
Base Material ◽  
Carbide Powder ◽  
Electrode Wear ◽  
Powder Concentration ◽  
Optimization Of Process Parameters ◽  
Recast Layer Thickness ◽  
Grey Relational ◽  
Pulse On Time

The present chapter deals with the investigations on the effect of process parameters like powder concentration (Cp), peak current (Ip), pulse-on-time (Ton), duty cycle (DC), and gap voltage (Vg) on output responses like material removal rate (MRR), tool wear rate (TWR), electrode wear ratio (EWR), surface roughness (SR), recast layer thickness (RLT), and micro-hardness (HVN) for PMEDM of H-11 hot work tool steel. Multi-objective optimization using grey relational analysis (GRA) has been implemented to identify the optimum set of input parameters to achieve maximum MRR and HVN with minimum TWR, EWR, SR, and RLT at the same time. Predicted results on verification with confirmation tests improve the preference values by 0.09468 with GRA. The recommended settings of process parameters is found to be Cp=6g/l, Ip=3Amp, Ton=100µs, DC=70%, and Vg=30V from GRA. The microstructures were examined with scanning electron microscope (SEM) to find the presence of surface deformities and identify alterations on the surface in comparison to the base material.

Multi-Objective Optimization of Machining Process Parameters in Wire-Cut Electric Discharge Machining of Inconel X750 Alloy by Combinatorial Approach

2019 ◽  
Vol 969 ◽  
pp. 781-786 ◽  
Author(s):  
G. Venkata Ajay Kumar ◽  
M. Shilpa ◽  
Udagave Shital Purander ◽  
G. Madhoo ◽  
V. Asokan
Keyword(s):  
Process Parameters ◽  
Electric Discharge ◽  
Removal Rate ◽  
High Hardness ◽  
Machining Process ◽  
Machining Processes ◽  
Grey Relational ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Conventional Machining

Difficult-to-cut materials, generally high hardness, strength and toughness, are generally difficult to machine in conventional machining. Also tool wear is high in conventional machining processes. Wire Cut Electric Discharge (WEDM) machining is particularly used for machining complex profiles, demanding very high accuracy. The current work focuses on the optimization of roughness of a surface that is machined using WEDM; the process parameters considered for optimization are pulse-on-time (Pon), pulse-off time (Poff), wire feedrate (WFR) and spark gap voltage (SGV). One of the surface integrity aspect is considered as surface roughness (SR) and other related to machining output considered as material removal rate (MRR) for the output responses. The paper presents, a multi-criteria decision making technique, with Grey Relational Analysis (GRA) integrated with Particle Swarm Optimization (PSO) for optimizing the process parameters. Further, confirmation tests that were conducted also validated the improvement in SR and MRR.

Sign in / Sign up

Export Citation Format

Share Document