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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- 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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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