Statistical and Numerical Approaches for Modeling and Optimizing Laser Micromachining Process-Review

Shadi M. Karazi, Mahmoud Moradi, Khaled Y. Benyounis

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

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.
Original languageEnglish
Title of host publicationReference Module in Materials Science and Materials Engineering
PublisherElsevier
DOIs
Publication statusE-pub ahead of print - 29 Apr 2019
Externally publishedYes

Publication series

NameReference Module in Materials Science and Materials Engineering

Fingerprint Dive into the research topics of 'Statistical and Numerical Approaches for Modeling and Optimizing Laser Micromachining Process-Review'. Together they form a unique fingerprint.

Cite this