| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_4ddcb273a108a5d8472b335280098e06 |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F2218-02 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/B30B15-26
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-048
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-084
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G05B23-027
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/B30B15-0094
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-214
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G05B23-024
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G05B23-0221 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/B30B15-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/B30B15-26
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G05B23-02 |
| filingDate |
2020-07-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_1a47d47e31607a03b56da115a2436302 |
| publicationDate |
2022-04-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
EP-3976365-A1 |
| titleOfInvention |
Separation of states of mechanical presses by analysing trained patterns in a neural network |
| abstract |
The present invention is related to a computer-implemented method of, a data processing system for and a computer program product for indicating a failure of a manufacturing process as well as to a corresponding manufacturing machine and further to a computer- implemented method of training a machine learning system (MLS) for indicating states of a manufacturing process. An input signal of a sensor is transformed into a parameter. The parameter is provided to the MLS, which derives latent features. The latent features are mapped into one of several distinct clusters each representing a mode of the manufacturing process. Finally, a failure of the manufacturing process based on the different states of the manufacturing process may be indicated. |
| priorityDate |
2019-08-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |