dc.contributor.author |
Kontolatis, N |
en |
dc.contributor.author |
Vosniakos, G-C |
en |
dc.date.accessioned |
2014-03-01T02:11:51Z |
|
dc.date.available |
2014-03-01T02:11:51Z |
|
dc.date.issued |
2012 |
en |
dc.identifier.issn |
09565515 |
en |
dc.identifier.uri |
https://dspace.lib.ntua.gr/xmlui/handle/123456789/29965 |
|
dc.subject |
Collision detection |
en |
dc.subject |
Dimensional accuracy |
en |
dc.subject |
Genetic algorithms |
en |
dc.subject |
Process planning |
en |
dc.subject |
Sheet bending |
en |
dc.subject.other |
3-D problems |
en |
dc.subject.other |
3-D space |
en |
dc.subject.other |
Bending sequence |
en |
dc.subject.other |
Collision detection |
en |
dc.subject.other |
Dimensional accuracy |
en |
dc.subject.other |
Expert knowledge |
en |
dc.subject.other |
Expert rule |
en |
dc.subject.other |
Handling time |
en |
dc.subject.other |
Interference detection |
en |
dc.subject.other |
Mechanical parts |
en |
dc.subject.other |
Optimisations |
en |
dc.subject.other |
Sheet bending |
en |
dc.subject.other |
Sheet metal bending |
en |
dc.subject.other |
Stochastic search |
en |
dc.subject.other |
Bending (forming) |
en |
dc.subject.other |
Genetic algorithms |
en |
dc.subject.other |
Process planning |
en |
dc.subject.other |
Sheet metal |
en |
dc.subject.other |
Three dimensional |
en |
dc.subject.other |
Optimization |
en |
dc.title |
Optimisation of press-brake bending operations in 3D space |
en |
heal.type |
journalArticle |
en |
heal.identifier.primary |
10.1007/s10845-010-0384-5 |
en |
heal.identifier.secondary |
http://dx.doi.org/10.1007/s10845-010-0384-5 |
en |
heal.publicationDate |
2012 |
en |
heal.abstract |
Sheet metal bending processes are applied in a multitude of mechanical parts. The process involves optimising the sequence of designated bends taking into account the total processing and handling time, avoiding collisions of the sheet metal with tools and machine and respecting the dimensional accuracy constraints of the part. Experienced operators employ expert rules to define possible different feasible sub-optimal sequences that lead to the desired final shape. The expert knowledge is replaced in this work by stochastic search using a classic genetic algorithm. In addition, dimensional accuracy issues are introduced by determining machine stopper positions. Interference detection libraries employed in connection to the search nature of the approach enabled coping with the full 3D problem instead of quasi 2D problems dealt with in literature. Optimum bending sequence, respective suitable bending tools and machine stopper positions for each bending stage result from the algorithm and are demonstrated with examples. © Springer Science+Business Media, LLC 2010. |
en |
heal.journalName |
Journal of Intelligent Manufacturing |
en |
dc.identifier.doi |
10.1007/s10845-010-0384-5 |
en |
dc.identifier.volume |
23 |
en |
dc.identifier.issue |
3 |
en |
dc.identifier.spage |
457 |
en |
dc.identifier.epage |
469 |
en |