MANON Lab
Many companies lack a consistent and traceable link between design and production or assembly planning. Whether a component is technically feasible to manufacture or what is needed to best assemble an assembly often depends on the experience and knowledge of individual persons. This leads to follow-up questions, unnecessary iterations and delays, especially in early phases such as quotation preparation, development and production planning. At the same time, variant diversity and time pressure are increasing, and in the event of bottlenecks, alternative machines, technologies or assembly processes must be found quickly. The status quo lacks easy-to-use digital tools that support decisions in a transparent manner.
MANON was developed as a scientific prototype at the Institute of Data Science. It analyses CAD models and maps knowledge about component characteristics, manufacturing processes and machines in a digital knowledge model. In the MANON Lab transfer project, we are transforming the prototype into a market-ready product. To this end, we are improving its robustness, usability and connectivity to industrial workflows. We are expanding MANON's technical capabilities in the direction of robotised assembly by systematically modelling assembly features, constraints and the capabilities of robots and tools. This results in comprehensible suggestions as to which assembly or manufacturing options are suitable and which boundary conditions are decisive. Our institute contributes special expertise in knowledge management with ontologies and knowledge graphs, as well as in the development of explainable systems.
MANON opens up new avenues for adaptive assembly in robotics: instead of rigid programmes, knowledge-based models support the planning and adaptation of assembly processes, for example when assemblies, tools or available robots change. This reduces coordination efforts, improves planning quality and reduces dependence on scarce expert knowledge. We create a scalable basis for more closely linking robotics, assembly planning and digital manufacturing assistance, and for developing future projects for resilient, knowledge-based automation.
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Project duration: 04/2026 - 03/2028