Toro, Cinthya Lasorsa, Carlos Sanchez Ake, Citlali Villagran-Muniz, M. Rinaldi, Carlos
Comis Nacl Energia Atom San Martin Buenos Aires ArgentinaUniv Tecnol Nacl UTN Regional Haedo ArgentinaUniv Nacl Autonoma Mexico CCADET Lab Fotofis Mexico City DF Mexico
摘要:
The technique of micro-machining assisted by laser is the most recent and flexible process for the design of complex devices. To be able to micro-machine hard materials with precision it is necessary to study the parameters that control and limit the capabilities of this laser process. Several articles have shown that if it applies a lot of energy in a localized area there are hot-affected zones (HAZ), even when a femtosecond laser is used. Hence, the challenge in the laser-based micromachining is to improve the quality of machining, i.e. depleting the HAZ in the prototypes. In this work, changing the optical properties of the substrate, good quality silicon micro-machining has been obtained with a nanosecond Q-switched laser. DOI:10.2961/jlmn.2012.03.0007
摘要:
There are several electrical and non-electrical factors having the significant effect on tool wear in electrical discharge machining (EDM). It is very difficult to select the parameters correctly. Likewise, the tool wear rate is changed dramatically with workpiece material and electrode material. Until now no attempt is appeared that yields the tool wear characteristics in EDM on Ti-5Al-2.5Sn retaining Graphite as electrode. Thus, in this study a mathematical model is developed to predict the tool wear rate which will provide the opportunity of proper selection of the EDM parameters and make the EDM cost effective. To model both the linear and non-linear equation is applied using the experimental data which are obtained performing the experimentation as design of experiment. The developed model has been verified through analysis of variance ( ANOVA). The second-order non-linear model is found as appropriate as compared with a linear model. It is evidenced that the proposed model can effectively predict the tool wear rate (TWR) and adequately explains the variation in the machining parameters on TWR.