Ontology-Based Skill Description Learning for Flexible Production Systems
- Resource Type
- Conference
- Authors
- Himmelhuber, Anna; Grimm, Stephan; Runkler, Thomas; Zillner, Sonja
- Source
- 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) Emerging Technologies and Factory Automation (ETFA), 2020 25th IEEE International Conference on. 1:975-981 Sep, 2020
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Robotics and Control Systems
Production systems
Logic programming
Conferences
Semantics
Production planning
Companies
Ontologies
skill description learning
ontology-based
flexible manufacturing
semantic web
inductive logic programming
class expression learning
- Language
- ISSN
- 1946-0759
The increasing importance of resource-efficient production entails that manufacturing companies have to create a more dynamic production environment, with flexible manufacturing machines and processes. To fully utilize this potential of dynamic manufacturing through automatic production planning, formal skill descriptions of the machines are essential. However, generating those skill descriptions in a manual fashion is labor-intensive and requires extensive domain-knowledge. In this contribution an ontology-based semi-automatic skill description system that utilizes production logs and industrial ontologies through inductive logic programming is introduced and benefits and drawbacks of the proposed solution are evaluated.