Knowledge Graphs for Solution Sizing in Factory Automation


In this presentation we describe the data processing workflow and querying approach of an online, customer-facing application for the interactive sizing of automation solutions from Festo, a global leader in factory automation. The semantic application uses knowledge graph (KG) technologies to present customers a ranked selection of proper solutions out of millions of electric drive trains from given parameters such as working range, moving mass, travel time, etc.

The talk will provide insights to the KG relevant parts of the productive application such as:

  • transformation of product data into an RDF knowledge graph by using a R2RML driven ETL process
  • reasoning based on OWL RL and SWRL to infer product compatibility from technical interface specifications
  • enrichment of the KG with business related constraints and sales information via SPARQL-Update
  • high-performance querying using a cascade of concurrent SPARQL queries that involve complex technical filter and ranking conditions


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