Empirical Modeling & Optimization of Laser Micro - Machining Process Parameters Using Genetic Algorithm

Autor: M. L. S. Deva Kumar, G. Harinath Gowd, V. Chengal Reddy
Rok vydání: 2018
Předmět:
Zdroj: Materials Today: Proceedings. 5:8095-8103
ISSN: 2214-7853
DOI: 10.1016/j.matpr.2017.11.496
Popis: The research has been originated based on the persuasive applications of Lasers in Automotive, Aerospace, Electronic and Heavy manufacturing industries to machine a variety of metals and alloys. Among all machining processes, Laser Beam Machining has turned to be the best one since it furnishes quick material removal with an effectively controlled, non-contact, non-wearing tool, involves highly localized heat input to the work piece, reduces distortion, and offers no tool wear, diminishes tendency of cracking. This paper focuses on understanding the impact of laser process parameters on the final geometrical and surface nature of micro-channel features fabricated on Hastelloy C276. Ideal choice of process parameters is highly critical for successful material removal and high dimensional and surface quality for micro-sized die/mold applications. Full factorial plan is utilized to do the test outline. A few micro-channels have been fabricated as miniaturized scale shape holes varying different process parameters. The connection between process parameters and quality attributes has been examined with experimental modeling. The set up models were utilized for optimizing the process parameters using Genetic Algorithm.
Databáze: OpenAIRE