Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : genetic algorithms

Optimization of Cutting Parameters in Milling Process Using Genetic Algorithm and ANOVA (March 2020)

Marwa Q. Ibraheem

Engineering and Technology Journal, 2020, Volume 38, Issue 10A, Pages 1489-1503
DOI: 10.30684/etj.v38i10A.1124

In this present work use a genetic algorithm for the selection of cutting conditions in milling operation such as cutting speed, feed and depth of cut to investigate the optimal value and the effects of it on the material removal rate and tool wear. The material selected for this work was Ti-6Al-4V Alloy using H13A carbide as a cutting tool. Two objective functions have been adopted gives minimum tool wear and maximum material removal rate that is simultaneously optimized. Finally, it does conclude from the results that the optimal value of cutting speed is (1992.601m/min), depth of cut is (1.55mm) and feed is (148.203mm/rev) for the present work.

Vibration Analysis of Laminated Composites Using Experimental and Genetic Algorithms Optimization Technique

Nabil Hassan Hadi; Kayser Aziz Ameen

Engineering and Technology Journal, 2012, Volume 30, Issue 18, Pages 3192-3218

In this paper, damage detection for different types of defects (delamination, crack
and hole) in the composite laminate plate and cylindrical shell be used to characterize
the vibration behavior experimentally which used two types of load (plus and sine
load) to find the frequency response. To this end, some plates and cylindrical shells
are made using hand-lay-up process. Glass fiber is used as a reinforcement in the
form of bidirectional fabric and general purpose polyester resin as matrix for the
composite material of plates and cylindrical shells. From the results, the damage
detection by using the Genetic algorithms is investigated. Also, these experiments are
used to validate the results of free vibration obtained from the finite elements