An Inference-based Knowledge Reuse Framework for Historical Product and Production Information Retrieval

The reuse of past knowledge constitutes a key factor for improving manufacturing performance, during design, planning, and operational phases. However, valuable knowledge generated and associated to products and processes on a daily basis, remains implicit and its reusability is confined to a specific machine operator or within legacy IT databases. The work proposed in this paper introduces a framework to enable reusability of manufacturing knowledge through inference rules applied on manufacturing ontologies. Initially, a mechanism is used to access a Relational Database Management System (RDBMS) and through a rule-based approach, it exports the analogous ontological schema. The ontology constitutes the knowledge base and is stored in a knowledge repository. An inference engine is then used to query this repository and derive additional assertions, which are entailed from the base schema, on product, process, and resource. The method is developed in a web app, which offers to the users the capability to create, activate, and share rules and results on engineering topics. The effectiveness of the framework is validated using a real industrial case from a high-precision mould-making SME.