Anomalous Logline Detection Tool
- Project
- 17030 DayTiMe
- Description
- Machine problems can be detected in an early phase and solved, preventing failure or misfunction and thus standstill times
- Very short training phase, also after software version change
- Contact
- Rolf Neubert, Thunderbyte AI B.V.
- rolf.neubert@thunderbyte.ai
- Technical features
Input(s):
- log text files
- mixed content allowed
- no size restriction
- application knowledge
Main feature(s):
- Identifying single anomalous log lines
- AI/ML application, not rule based
- Taking context into account
Output(s):
- Anomalous line pointer
- In learning phase: feedback-form to teach what’s normal
- Integration constraints
- Service or development engineer, or annotated log files, needed for application-specific machine learning training
- Online access to logging computer, or local offline operation
- Processing power dependent on log file size and quantity
- Targeted customer(s)
Machine and Instrument application developers, any service supplier who could exploit routinely logged information files.
- Conditions for reuse
Commercial licence to be negotiated.
- Confidentiality
- Public
- Publication date
- 25-03-2022
- Involved partners
- Thunderbyte.AI (NLD)