We describe the derivation of ontology to capture knowledge regarding small series manufacturing. This work is motivated by use-cases ranging from the assembly of large aircraft built from about 6 million parts to the production of galley inserts, both plagued by problems for arising from the same interplay between product and production engineering. During ramp-up stages of such production, there are challenges of innovative technologies, high quality and safety standards or the structural complexity of products which frequently cause supply-chain problems or require revisions of the designs that result in significant financial losses. These conditions differ significantly from standard production scenarios. Based on a detailed domain analysis, we identify five requirements for the type of knowledge to be captured in ontology, and then proceed to propose a first version of such an ontology addressing these requirements, thus providing an appropriate semantic base for intelligent, associative tools that can effectively support ramp-up management. © 2013 Springer-Verlag.
CITATION STYLE
Inden, U., Mehandjiev, N., Mönch, L., & Vrba, P. (2013). Towards an ontology for small series production. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8062 LNAI, pp. 128–139). https://doi.org/10.1007/978-3-642-40090-2_12
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