Toward a Knowledge-Based Data Backbone for Seamless Digital Engineering in Smart Factories

Alexander Perzylo, Ingmar Kessler, Stefan Profanter and Markus Rickert

Proceedings of the IEEE International Conference on Emerging Technologies And Factory Automation (ETFA), pp. 164–171

September 2020 · Vienna, Austria · doi: 10.1109/ETFA46521.2020.9211943


Digital transformation efforts in manufacturing companies bear the potential to reduce product costs and increase the flexibility of production systems. The semantic integration of data and information along the value chain enables the automated interpretation of interrelations between its different aspects such as product design, production process and manufacturing resources. These interrelations can be used to automatically generate semantic process descriptions and execute corresponding robot motions. An initial one-time effort to model the required knowledge of a particular application domain can make the manufacturing of high-variant products in small batches or even lot size one production more efficient. This paper introduces a knowledge-based digital engineering concept to automate engineering and production activities without human involvement. The concept was integrated and evaluated in a physical robot workcell where automotive fuse boxes are autonomously fitted with different fuse configurations.

subject terms: robotics, data backbone