Manufacturing custom parts in several industry sectors has become challenging, especially in the aerospace industry. This factor is due to the complexity of the product, low manufacturing levels, and a competitive market in which it seeks to reduce the consumption of resources and optimise processes. Traditionally, the process of generating and analysing manufacturing plans is manual, in which a team of engineers analyses piece by piece and generates manufacturing plans for each customised part. In a complex product such as an aircraft, this number can exceed 500,000 parts. Disruptions due to project changes can lead to increased expenses, time investments, and environmental impacts. Based on this context, this paper discusses Ontology-Based Engineering (OBE) Systems for Knowledge-Driven Manufacturing using concepts such as Semantic Interoperability (SI), Automated Feature Recognition (AFR), Models for Manufacturing (MfM) and Large Language Model (LLM) to solve the problem of integration of data, information and knowledge at the stages of the production process. The proposed framework enables the seamless integration of digital and physical technologies, facilitating communication and transparency across the complex manufacturing process. Implementing the OBE system enhances manufacturing efficiency, reduces costs, and improves product quality in the aerospace industry. An experimental case showed the ability to store data and knowledge in a structured way and thus generate different manufacturing plans, supporting process decision-making. Future work will focus on validating the manufacturing plans generated by the system and comparing them with traditionally generated ones, with the objective of application in product development.