The accelerated advancement of manufacturing technologies has transformed traditional production paradigms, demanding intelligent, agile, and sustainable solutions to remain competitive in a dynamic market. Smart manufacturing leverages flexible automation, collaborative systems, and emerging technologies to address complex challenges such as interoperability, decision-making, and resilience in the multivariate context of the industrial environment. In this context, semantic technologies such as ontologies and knowledge graphs provide robust frameworks for structuring and integrating diverse data and processes to enable dynamic decision-making across domains. This research investigates the synergy between semantic technologies and AI-driven models, including generative approaches, to enhance interoperability and collaboration in manufacturing. The present work presents the development, implementation, and experimental application of a knowledge-based system for estimating product manufacturing costs. Additionally, the research discusses alternatives and future possibilities for the semantic alignment layer, underscoring the role of semantic structuring integrated with AI in bridging knowledge gaps and driving innovation in manufacturing processes.