Knowledge-based expert system to drive an informationally interoperable manufacturing system: An experimental application in the Aerospace Industry

The industrial revolutions have challenged organisations to rethink their product design and manufacturing processes, making them faster and more connected to market demands and changes. Digital technologies have emerged with solutions to virtual represent physical objects, processes, systems, or assets to simulate and analyse the impact of manufacturing changes before actual implementation. However, the challenge is to deal with thousands of heterogeneous information sets which must be shared simultaneously by different groups within and across institutional boundaries. Each manufacturing industry has its format and model to represent the product in the development, manufacturing process, material features, etc. In this context, this paper explores a knowledge-based expert system to support the information exchange and inconsistency detection across the manufacturing process, specifically in an experimental application in the Aerospace Industry. The proposed framework was based on knowledge formalisation and semantic rules through ontologies, semantic reconciliation strategies and connectivity interfaces to manage information and knowledge and identify inconsistencies across the manufacturing system. It was mainly evaluated across the product and manufacturing design of sheet metal forming aluminium thin wall parts for the aerospace industry. Results demonstrate the capability of the approach to enhance data accuracy, coherence, and efficiency throughout the manufacturing of complex products. However, the solution presents challenges such as interdisciplinary collaboration in product design, specific information requirements for manufacturing planning, and the impact of production planning on manufacturing capacities.