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A standard deviation based firefly algorithm for multi-objective optimization of WEDM process during machining of Indian RAFM steel

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Abstract

Non-conventional machining processes always suffer due to their low productivity and high cost. However, a suitable machining process should improve its productivity without compromising product quality. This implies the necessity to use efficient multi-objective optimization algorithm in non-conventional machining processes. In this present paper, an effective standard deviation based multi-objective fire-fly algorithm is proposed to predict various process parameters for maximum productivity (without affecting product quality) during WEDM of Indian RAFM steel. The process parameters of WEDM considered for this study are: pulse current (I), pulse-on time (T on), pulse-off time (T off) and wire tension (WT).While, cutting speed (CS) and surface roughness (SR) were considered as machining performance parameters. Mathematical models relating the process and response parameters had been developed by linear regression analysis and standard deviation method was used to convert this multi objective into single objective by unifying the responses. The model was then implemented in firefly algorithm in order to optimize the process parameters. The computational results depict that the proposed method is well capable of giving optimal results in WEDM process and is fairly superior to the two most popular evolutionary algorithms (particle swarm optimization algorithm and differential evolution algorithm) available in the literature.

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Abbreviations

I :

Pulse current

T on :

Pulse-on time

T off :

Pulse-off time

WT:

Wire tension

CS:

Cutting speed

min CS:

The minimum value of cutting speed

max CS:

The maximum value of cutting speed

SR:

Surface roughness

min SR:

The minimum value of surface roughness

max SR:

The maximum value of surface roughness

FA:

Firefly algorithm

PSO:

Particle swarm optimization algorithm

DE:

Differential evolution algorithm

RAFM:

Reduced activation ferritic martensitic steel

WEDM:

Wire electrical discharge machining

r :

Distance between two fire-fly

I(r):

Light intensity at distance (r)

I 0 :

Original light intensity at zero distance

γ :

Light absorption coefficient

β :

Attractiveness measure at distance (r)

β 0 :

Original attractiveness at zero distance

x i *(k):

Normalized value of output parameter ‘i’ at kth experiment

x (o) i (k):

Experimental value of output parameter ‘i’ at kth experiment

minx (o) i (k):

The minimum value of output parameter ‘i’

maxx (o) i (k):

The maximum value of output parameter ‘i’

ν i :

Variances of normalized output parameter ‘i’

μ i :

Mean of all normalized experimental values (n) for output parameter ‘i’

n :

Number of experiments

w 1, w 2 :

Individual response weight of cutting speed and surface roughness respectively

N :

Population size/size of the swarm

T :

Number of iteration

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Authors and Affiliations

  1. Mechanical Engineering Department, National Institute of Technology-Agartala, Agartala, Tripura, 799046, India

    Arindam Majumder, Argha Das & Pankaj Kr. Das

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  1. Arindam Majumder
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  2. Argha Das
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  3. Pankaj Kr. Das
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Correspondence to Arindam Majumder.

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Majumder, A., Das, A. & Das, P.K. A standard deviation based firefly algorithm for multi-objective optimization of WEDM process during machining of Indian RAFM steel. Neural Comput & Applic 29, 665–677 (2018). https://doi.org/10.1007/s00521-016-2471-9

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  • DOI: https://doi.org/10.1007/s00521-016-2471-9

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