Towards a Knowledge-Augmented Socio-Technical Assistance System for Product Engineering

Dominik Mittel , Andreas Hubert , Junsheng Ding und Alexander Perzylo

Proceedings of the IEEE International Conference on Emerging Technologies And Factory Automation (ETFA),

September 2023 · Sinaia, Romania · DOI: 10.1109/ETFA54631.2023.10275386

Zusammenfassung

Digital tools for handling the whole product engineering phase are getting more and more important in the context of Industry 4.0 and an increasing product variety. However, especially in small and medium-sized enterprises, a lot of information about product development and production is stored in different documents or isolated data silos. A promising way to arrive at a solution is to model data and knowledge with ontologies and enrich it with context information. This paper presents a concept and a showcase implementation of a company-internal and personalized assistance system for an end-to-end digital product engineering process. We combine a generic and cost-efficient human assistance solution focusing on social aspects and a company-wide knowledge graph to create a seamless and highly integrated data structure that assists many stakeholders in the product engineering process, from product designers to assembly workers. As a result, more complex products can be handled and the product engineering process can be accelerated.

Stichworte: peng, diprolea

Url: https://mediatum.ub.tum.de/doc/1725357/1725357.pdf