# Ontology-Based Skill Description Learning for Flexible Production Systems

arXiv: https://arxiv.org/abs/2111.13142 · HTML: https://mlsanity.com/paper/2111.13142/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 16 references that are in the map.
- First posted on arXiv 25 Nov 2021.

## Built on by (most cited first, 2 of 2)

- [A Research Agenda for AI Planning in the Field of Flexible Production Systems](https://mlsanity.com/paper/2112.15484/) (2021)
- [Capabilities and Skills in Manufacturing: A Survey Over the Last Decade of ETFA](https://mlsanity.com/paper/2204.12908/) (2022)

## Abstract (arXiv)

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.