| dc.contributor.author |
Chandrasekaran, M |
|
| dc.contributor.author |
Devarasiddappa, D |
|
| dc.date.accessioned |
2014-07-23T09:08:25Z |
|
| dc.date.available |
2014-07-23T09:08:25Z |
|
| dc.date.issued |
2014-06-01 |
|
| dc.identifier.issn |
1854-6250 |
|
| dc.identifier.uri |
http://dyuthi.cusat.ac.in/purl/4267 |
|
| dc.description |
Advances in production engineering and management,vol 9 no 2,pp 59-70 |
en_US |
| dc.description.abstract |
Metal matrix composites (MMC) having aluminium (Al) in the matrix phase and silicon
carbide particles (SiCp) in reinforcement phase, ie Al‐SiCp type MMC, have gained
popularity in the re‐cent past. In this competitive age, manufacturing industries strive to
produce superior quality products at reasonable price. This is possible by achieving higher
productivity while performing machining at optimum combinations of process variables. The
low weight and high strength MMC are found suitable for variety of components |
en_US |
| dc.description.sponsorship |
CUSAT |
en_US |
| dc.language.iso |
en |
en_US |
| dc.subject |
metal matrix composites |
en_US |
| dc.subject |
culindrical grinding |
en_US |
| dc.subject |
surface roughness |
en_US |
| dc.subject |
artificial neural network |
en_US |
| dc.subject |
analysis of variance |
en_US |
| dc.title |
Artificial neural network modeling for surface roughness prediction in cylindrical grinding of Al‐SiCp metal matrix composites and ANOVA analysis |
en_US |
| dc.type |
Article |
en_US |