Abstract
Optimization of cutting parameters is valuable in terms of providing high precision and efficient machining. Optimization of machining parameters for milling is an important step to minimize the machining time and cutting force, increase productivity and tool life and obtain better surface finish. In this work a mathematical model has been developed based on both the material behavior and the machine dynamics to determine cutting force for milling operations. The system used for optimization is based on powerful artificial intelligence called genetic algorithms (GA). The machining time is considered as the objective function and constraints are tool life, limits of feed rate, depth of cut, cutting speed, surface roughness, cutting force and amplitude of vibrations while maintaining a constant material removal rate. The result of the work shows how a complex optimization problem is handled by a genetic algorithm and converges very quickly. Experimental end milling tests have been performed on mild steel to measure surface roughness, cutting force using milling tool dynamometer and vibration using a FFT (fast Fourier transform) analyzer for the optimized cutting parameters in a Universal milling machine using an HSS cutter. From the estimated surface roughness value of 0.71 μm, the optimal cutting parameters that have given a maximum material removal rate of 6.0×103 mm3/min with less amplitude of vibration at the work piece support 1.66 μm maximum displacement. The good agreement between the GA cutting forces and measured cutting forces clearly demonstrates the accuracy and effectiveness of the model presented and program developed. The obtained results indicate that the optimized parameters are capable of machining the work piece more efficiently with better surface finish.
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Abbreviations
- A :
-
Cross-sectional area of chip (mm)
- b :
-
Axial depth of cut (mm)
- b r :
-
Radial depth of cut (mm)
- D :
-
Diameter of cutting tool (mm)
- L :
-
Length of work piece (mm)
- F N :
-
Radial force (N)
- F T :
-
Thrust force (N)
- f :
-
Feed rate per tooth (mm/tooth)
- f W :
-
Table feed rate (work piece feed rate), mm/min
- F x , y :
-
Cutting force component in directionx andy (N)
- h :
-
Chip thickness (mm)
- k :
-
Stiffness of the cutter (N/mm)
- m :
-
Average number of teeth in contact with work piece
- N :
-
Rotational speed of milling cutter (rpm)
- R a :
-
Value of surface roughness (μm)
- T :
-
Tool life (min)
- V :
-
Cutting speed (m/min)
- x :
-
Dynamic displacement in feed direction x (mm)
- y :
-
Dynamic displacement in normal direction y (mm)
- Z :
-
Number of teeth on the cutting tool
- φ :
-
Rotational position of cutting edge (degrees)
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Palanisamy, P., Rajendran, I. & Shanmugasundaram, S. Optimization of machining parameters using genetic algorithm and experimental validation for end-milling operations. Int J Adv Manuf Technol 32, 644–655 (2007). https://doi.org/10.1007/s00170-005-0384-3
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DOI: https://doi.org/10.1007/s00170-005-0384-3