Work

Structured Product Engineering: Ontology-based Advanced Product Quality Planning

Year: 2026

Type: article

Abstract: Increasingly complex products make it difficult to efficiently meet customer requirements and underline the need for structured product engineering. Ontologies enable the combination of heterogeneous data sources and linking of existing knowledge to automatically derive further insights. In this work, an ontology-based approach for a structured product engineering process is introduced. We develop an ontology for Advanced Product Quality Planning (APQP)-guided product development and combine it with semantic models regarding production knowledge, ontology-based geometric representations, and a graphical user interface. As a result, an assistance system that provides support from customer inquiry to product design is developed.

Source: Procedia CIRP

DOI: 10.1016/j.procir.2026.01.191

Authors: Uppili Srinivasan, Dominik Mittel, Daniel Lemberger, Alexander Perzylo

Institutions: Fortiss, Technical University of Munich

Language: English

Topic: Semantic Web and Ontologies

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funder: Bundesministerium für Bildung und Forschung

Award: Verbundprojekt: Entwicklung eines durchgängig digitalen Produktionsprozesses mit lernendem Assistenzsystem (DiProLeA), Teilprojekt:Seemantische Integration von prozessrelevanten Informationen und Kommunikation, automatisierte Ableitung von Arbeitsanweisungen