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Taguchi- Grey Theory Based Harmony Search Algorithm (GR-HSA) for Predictive Modeling and Multi-Objective Optimization in Drilling of Polymer Composites

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Abstract

This paper deals with a new hybridization methodology of Grey integrated Harmony search algorithm (GR-HSA) for predictive modeling. Simultaneously, parametric optimization during drilling of Graphite reinforced epoxy composites using the TiAlN coated SiC drill. Three process constraints namely spindle speed (N), feed (F), and wt.% of Graphite (G%), varied at four discrete levels, and Taguchi-based L16 orthogonal array used for experimentation. Machining performance is considered as material removal rate (MRR), thrust force (Th), torque (T), and surface roughness (Ra). A statistical model was established between input and output functions. Multiple performances are aggregated into an objective function known as Grey relation grade (GRG). Non-linear regression analysis inveterates the fitness function to the implementation of the Harmony search algorithm. The outcome revealed that the GR-HSA module shows the higher application potential with an improvement of 3.55% over the traditional GRA-Taguchi method. Further, high resolution scanning analysis was made to evaluate the quality of the drilled hole. The results inferred that spindle speed in the case of GR-HSA (2500 rpm) increases the temperature between the machining interface, which softens the polymeric material of the machining zone. This, in turn, gives a lower value of thrust force with improved surface finishing. The results of the scanning test demonstrate the feasibility of the GR-HSA hybrid method.

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Abbreviations

GRA:

Grey Relation Analysis

GRC:

Grey Relation Coefficient

GRG:

Grey Relation Grade

GFRP:

Glass fiber reinforced polymer

FRP:

Fiber reinforced polymer

HSA:

Harmony Search Algorithm

GR-HSA:

Grey Relation-Harmony Search Algorithm

N:

Spindle Speed

F:

Feed

G%:

wt.% of Graphite

MRR:

Material Removal Rate

Th:

Thrust Force

T:

Torque Force

Ra:

Surface Roughness

ANOVA:

Analysis of Variance

MPI:

Multi Performance Index

GA:

Genetic Algorithm

SA:

Simulation Annealing

PSO:

Particle Swarm Optimisation

ABC:

Artificial Bee Colony

Wt.%:

Weight percentage

ATR IR:

Attenuated Total Reflection internally reflected

DSC:

Differential scanning calorimetry

PCL poly:

Polycaprolactone polymer

OH:

Hydrogen Oxide

GrlBi:

Bismaleimide graphite fiber

RSM:

Response surface methodology

DFA:

Desirability Function Analysis

OA:

Orthogonal Array

DDM:

Diamino Diphenyl Sulfone

MPa:

Mega Pascal

min:

Minute

mm:

Milli meter

CNC:

Computer Numerical Control

Nm:

Newton Meter

N:

Newton

LB:

Lower is Better

HB:

Higher is Better

S/N:

Signal to Noise

N :

Normalize

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Acknowledgments

The authors are very thankful to the National Institute of Technical Teachers Training and Research, Kolkata, India, for affording all feasible help in carrying out this experimentation directly or indirectly.

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This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, 273010, India

    J. Kumar & R.K. Verma

  2. Department of Mechanical Engineering, National Institute of Technical Teachers Training and Research, Kolkata, 700106, India

    A.K. Mondal

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Kumar, J., Verma, R. & Mondal, A. Taguchi- Grey Theory Based Harmony Search Algorithm (GR-HSA) for Predictive Modeling and Multi-Objective Optimization in Drilling of Polymer Composites. Exp Tech 45, 531–548 (2021). https://doi.org/10.1007/s40799-020-00428-y

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