TY - CHAP
T1 - Statistical and Numerical Approaches for Modeling and Optimizing Laser Micromachining Process-Review
AU - Karazi, Shadi M.
AU - Moradi, Mahmoud
AU - Benyounis, Khaled Y.
PY - 2019
Y1 - 2019
N2 - This article presents the modeling and optimization techniques commonly used in engineering applications especially in Laser Micromachining process. Design of Experiment DOE (Response Surface Method and Taguchi), Artificial Neural Network (ANN), Genetic Algorithm (GA), and Particle swarm optimization (PSO) and mixed techniques are explained briefly. Furthermore, a review of laser micromachining processes parameters optimization was studied. Recent researches which used different approaches for modeling and optimization was presented.
AB - This article presents the modeling and optimization techniques commonly used in engineering applications especially in Laser Micromachining process. Design of Experiment DOE (Response Surface Method and Taguchi), Artificial Neural Network (ANN), Genetic Algorithm (GA), and Particle swarm optimization (PSO) and mixed techniques are explained briefly. Furthermore, a review of laser micromachining processes parameters optimization was studied. Recent researches which used different approaches for modeling and optimization was presented.
UR - https://www.mendeley.com/catalogue/3907cd93-717a-3125-ada0-a3b7d4bac538/
U2 - 10.1016/b978-0-12-803581-8.11650-9
DO - 10.1016/b978-0-12-803581-8.11650-9
M3 - Chapter
T3 - Reference Module in Materials Science and Materials Engineering
BT - Reference Module in Materials Science and Materials Engineering
PB - Elsevier
ER -