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Dimensional accuracy improvement by parametric optimization in pulsed Nd:YAG laser cutting of Kevlar-29/basalt fiber-reinforced hybrid composites

  • Girish Dutt GautamEmail author
  • Dhananjay R. Mishra
Technical Paper
  • 32 Downloads

Abstract

Laser cutting proves its suitability for cutting of single fiber-reinforced polymer (FRP) composites compared with conventional cutting techniques due to reduced fiber delamination, matrix cracking and fiber pullout. However, the performance of the laser cutting process of hybrid FRP composites is yet to be revealed, which paves the way of the present study. In this article, an experimental investigation of the laser cutting process is carried out on 1.35-mm-thick Kevlar-29 and basalt fiber-reinforced polymer (KBFRP) hybrid composite laminates using 250 W pulsed Nd:YAG laser system. The performance of laser cutting was evaluated by quantifying different kerf quality characteristics such as top and bottom kerf width, top and bottom kerf deviation and kerf taper. These kerf quality characteristics define the geometrical accuracy of the laser cut. Response surface methodology-based Box–Behnken design was adopted for conducting the experiments with varied settings of laser cutting parameters, viz. lamp current, pulse width, pulse frequency, compressed air pressure and cutting speed. Second-order regression models of each response were developed and validated by using standard error plots. A parametric effect analysis was carried out by using the variation of performance measures predicted through developed mathematical models. In order to achieve the optimal levels of the process parameters for all kerf quality characteristics, a self-developed python language-coded TLBO algorithm was used. Finally, the confirmation experiments were performed at obtained optimal levels of laser cutting parameters. An overall improvement of 22.23% in multiple kerf quality characteristics was achieved through optimal settings of laser cutting parameters. The individual improvement of 11.44%, 8.47%, 17.65%, 15.22% and 58.87% was recorded in top kerf width, bottom kerf width, top kerf deviation, bottom kerf deviation and kerf taper, respectively. The developed mathematical models and suggested optimal conditions are able to provide direction to the researchers for obtaining higher-dimensional accuracy in Nd:YAG laser cutting of KBFRP hybrid composites.

Keywords

Laser beam cutting Hybrid FRP composite Pulsed Nd:YAG laser Kerf quality characteristics Optimization TLBO algorithm 

List of symbols

b0, bii and bij

Regression coefficients

f

Pulse frequency (Hz)

F value

F test value

I

Lamp current (A)

K1, K2, …, K6

Replications of kerf width measurement

Kbest

Result of the best learner for a particular subject

m

Number of subjects

n

Number of learners

Mij

Mean of results for particular subject ‘j’ (j = 1, 2, 3, …, m)

p

Compressed air pressure (kg/cm2)

P value

Probability value

PW

Pulse width (ms)

ri

Random number between 0 and 1

R2

Regression coefficient of determination

R2 adj.

Adjusted regression coefficient of determination

S

Cutting speed (mm/min)

S value

Standard deviation

TF

Teaching factor in the range between 1 and 2

W1, W2, W2, W3, W4 and W5

Assigned weights for functions Z1, Z2, Z3, Z4 and Z5, respectively

xij

Values of laser parameters for ith observation and jth level

Xj, kbest, i

Result of the best learner in subject j

y

Output response

Z

Normalized combined objective function

Z1, Z2, Z3, Z4 and Z5

Regression models of TKW, BKW, TKD, BKD and KT, respectively

Z1(min), Z2(min), Z3(min), Z4(min) and Z5(min)

Minimum values of TKW, BKW, TKD, BKD and KT, respectively

Abbreviations

ANOVA

Analysis of variances

BKD

Bottom kerf deviation

BKW

Bottom kerf width

CFRP

Carbon fiber-reinforced polymer

DOE

Design of experiments

FRP

Fiber-reinforced polymer

GFRP

Glass fiber-reinforced polymer

GRA

Grey relational analysis

HAZ

Heat-affected zone

KBFRP

Kevlar-29/basalt fiber-reinforced polymer

KFRP

Kevlar fiber-reinforced polymer

KT

Kerf taper

LBC

Laser beam cutting

Nd:YAG

Neodymium-doped yttrium aluminum garnet

RSM

Response surface methodology

TKD

Top kerf deviation

TKW

Top kerf width

TLBO

Teaching–learning-based optimization algorithm

Notes

Acknowledgements

The authors sincerely express their heartiest thanks to Dr B.N. Upadhayay, SOF, Solid State Division of RRCAT (Raja Ramanna Centre for Advanced Technology), Indore (MP), for providing the experimental support for this work. The authors are also grateful to the management of Jaypee University of Engineering and Technology, Guna (MP), India, for their laboratory and financial assistance to carry out this research work.

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Copyright information

© The Brazilian Society of Mechanical Sciences and Engineering 2019

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringJaypee University of Engineering & TechnologyGunaIndia

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