Name: Parametric control in EDM and development of Mathematical correlations (en Inglés)
Price: 289.03 PEN
Availability: InStock
Author: Macharla, Srinivasa Rao ; Singu, Sivanaga Malleswararao
ISBN: 9786139452774

portada Parametric control in EDM and development of Mathematical correlations (en Inglés)

Formato

Libro Físico

Autor

Srinivasa Rao Macharla

Sivanaga Malleswararao Singu

Editorial

LAP Lambert Academic Publishing

Idioma

Inglés

N° páginas

152

Encuadernación

Tapa Blanda

Dimensiones

22.9 x 15.2 x 0.9 cm

Peso

0.23 kg.

ISBN13

9786139452774

Categorías

Ingeniería: general

Parametric control in EDM and development of Mathematical correlations (en Inglés)

Srinivasa Rao Macharla (Autor) · Sivanaga Malleswararao Singu (Autor) · LAP Lambert Academic Publishing · Tapa Blanda

Libro Nuevo

S/ 289,03

S/ 578,06

Ahorras: S/ 289,03

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Origen: Estados Unidos (Costos de importación incluídos en el precio)

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Reseña del libro "Parametric control in EDM and development of Mathematical correlations (en Inglés)"

EDM is one of the unconventional machining process which is used widely in tooling sector. In EDM, it is necessary to optimize the process parameters such as pulse on-time, pulse off-time, discharge current and voltage for maximization of MRR and minimization of Tool Wear Rate (TWR) for various work piece materials. Titanium (Ti-6Al-4V) and HC-HCr Steel are considered for the experimentation in the present research as these are widely used aerospace, robotics, automotive and tooling sectors. DOE have been conducted at different levels of pulse on-time, pulse off-time, discharge current and voltage. The design of experiments is carried out by varying the input parameters and derived the optimal mathematical correlations to get maximum MRR and minimum TWR. Copper and EDM oil are used as electrode and di-electric fluid respectively. Experimental results of MRR and tool wear rate were analyzed with responses surface methodology and presented various graphs. Interaction effect of process parameters on the responses has been discussed. MR optimization technique was used to optimize process parameters for minimum surface roughness and tool wear rate and maximum MRR.