Today's tool and die making industry is characterized by increased individualization and complex manufacturing processes. Therefore, toolmaking companies are forced to always push the limits of what is technically feasible. The usual heterogeneous use of different manufacturing technologies generates high manual planning efforts and requires a cross-technology process understanding. A large number of influencing and disturbing variables affect the individual process steps, which can be caused by individual production machines, peripherals or the entire production environment. Currently, this process knowledge is only available in individual and small batch production as implicit technical and experiential knowledge of long-term employees in the companies.
An OWL-based ontology is presented in order to make the described implicit technical and experiential knowledge of the employees usable on a long-term basis. Due to a very high semantic expressiveness, ontologies allow to represent even the most complex data models with logical relations beyond a pure hierarchical subdivision (taxonomy) of contents. In practice, they are increasingly used in knowledge management, natural language processing, e-commerce and information retrieval.
The proposed domain specific ontology allows a shared and common understanding of machines, work pieces, operating resources and manufacturing processes. The use of Semantic Web technologies makes it possible to pose concrete search queries to the system and, for example, to compare the actual performance of multiple milling machines with the theoretical performance. In addition, the developed domain-specific ontology enables the unambiguous referencing of specific tools (e.g. milling tools) used to manufacture a work-piece.
The developed ontology solves the problem of the non-existent possibility of merging manufacturing data and formalized classification of different manufacturing technologies and enables the use of implicit technical and experiential knowledge in tooling.