# KAPPS: A knowledge-based CPPS Architecture for the Circular Factory

arXiv: https://arxiv.org/abs/2605.22457 · HTML: https://mlsanity.com/paper/2605.22457/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 67 references that are in the map.
- First posted on arXiv 21 May 2026.

## Builds on (most cited first, 7 of 7)

- [A Reference Model for Common Understanding of Capabilities and Skills in Manufacturing](https://mlsanity.com/paper/2209.09632/) (2022)
- [Representing Timed Automata and Timing Anomalies of Cyber-Physical Production Systems in Knowledge Graphs](https://mlsanity.com/paper/2308.13433/) (2023)
- [Toward a Mapping of Capability and Skill Models using Asset Administration Shells and Ontologies](https://mlsanity.com/paper/2307.00827/) (2023)
- [Learning Symbolic and Subsymbolic Temporal Task Constraints from Bimanual Human Demonstrations](https://mlsanity.com/paper/2403.16953/) (2024)
- [Comprehensive Description of Uncertainty in Measurement for Representation and Propagation with Scalable Precision](https://mlsanity.com/paper/2603.20365/) (2026)
- [Mitigating Undesired Conditions in Flexible Production with Product-Process-Resource Asset Knowledge Graphs](https://mlsanity.com/paper/2508.06278/) (2025)
- [Toward Self-Organizing Production Logistics: A Multi-Agent Approach](https://mlsanity.com/paper/2604.04753/) (2026)

## Abstract (arXiv)

While linear manufacturing relies on homogeneous materials and predefined process sequences, circular manufacturing reintroduces used products with heterogeneous and uncertain conditions. This shift demands manufacturing systems capable of handling variable product states, dynamically reconfigurable processes, and the integration of human and machine knowledge. Conventional manufacturing IT architectures, designed for stable structures and deterministic execution, are unable to meet these requirements, as they cannot adequately represent and manage the uniqueness of individual components at runtime. Following a design science methodology for developing a Cyber Physical Production System for circular manufacturing, we derive 14 requirements from five complementary perspectives. Based on these requirements, we design KAPPS, a knowledge-based architecture that uses an ontology-grounded knowledge graph as a unifying data backbone, combined with a semantic interface layer to enable consistent data and information integration, reasoning, and communication across heterogeneous systems and services, turning the knowledge graph from an integration layer into the factories authoritative write-time state. KAPPS incorporates modules for constraint enforcement and event-driven planning, enabling incremental adaptation of execution plans under uncertainty and human-machine knowledge exchange. The applicability of KAPPS is demonstrated through two implemented use cases: (i) Anomaly detection and learning through knowledge graph mediated services and (ii) runtime constraint enforcement in a modular conveyor system. Subsequently, the architecture is evaluated against the 14 requirements (ed. abstract shortened)