EP 3969230 A1 20220323 - ARTIFICIAL INTELLIGENCE IN DISCRETE MANUFACTURING
Title (en)
ARTIFICIAL INTELLIGENCE IN DISCRETE MANUFACTURING
Title (de)
KÜNSTLICHE INTELLIGENZ IN DER DISKRETEN FERTIGUNG
Title (fr)
INTELLIGENCE ARTIFICIELLE DANS LA FABRICATION DISCRÈTE
Publication
Application
Priority
EP 2019062104 W 20190511
Abstract (en)
[origin: WO2020228932A1] The quality of a workpiece (6) can only be measured once it has been machined. If the workpiece (6) is to be rejected due to deviations, any correlation between these deviations and parameters of the NC program is not apparent. To improve the machining result, each candidate parameter of the NC program thus needs to be varied in a time-consuming trial- and-error procedure. Dynamic behavior of interpolator, position controller, and drive may hence be considered a "black box", the detailed functioning of these control modules remaining largely unclear. Also, the NC program is static and does not change during series production. Even if the behavior of the machines changes over a longer period due to aging, the NC program remains unchanged, resulting in a creeping degradation of workpiece quality. There is typically no adaptation to changing production conditions. As per the invention, machine learning techniques are used, for example, to predict production quality, to optimize, or to reduce the cycle time of CNC machining.
IPC 8 full level
B25J 9/16 (2006.01); G05B 13/02 (2006.01)
CPC (source: EP)
B25J 9/163 (2013.01); G05B 13/0265 (2013.01); G05B 2219/32194 (2013.01); G05B 2219/33321 (2013.01); G05B 2219/39271 (2013.01); Y02P 90/02 (2015.11); Y02P 90/80 (2015.11)
Citation (search report)
See references of WO 2020228932A1
Designated contracting state (EPC)
AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR
Designated extension state (EPC)
BA ME
DOCDB simple family (publication)
DOCDB simple family (application)
EP 2019062104 W 20190511; EP 19724411 A 20190511