KNOWLEDGE MANAGEMENT WITH AN INTELLIGENT TOOL FOR ADDITIVE MANUFACTURING

Manufacturers face the challenge of deciding when additive manufacturing technology offers a suitable process to produce a given product. Information needed about process capabilities is constantly evolving and usually not organized well enough to support such decisions. This work introduces an ontological framework which identifies and semantically models the most applicable concepts of additive manufacturing relevant to process planning applications. Another salient feature includes the fit of this structural framework with both the new ASTM standard for additive manufacturing vocabulary and existing taxonomies for traditional manufacturing processes. Finally, within this framework we implemented description logic rules to identify the optimal set of processes for a product, the rationale for selecting this set of processes, and a logical link between a product's features and its process plan. The reliability of the knowledge representation and its process planning capabilities are each tested and demonstrated by a case study example of the selection of the best processes to produce a steel spur gear.