Manufacturing ontologies play a crucial role in the architecture and improvements of manufacturing systems, particularly in the context of Industry 4.0. They provide an effective way to manage information and data from production systems by describing them in a common language, which is critical for digital transformation.
Also, Ontologies provide semantic support for sharing and accessing manufacturing-related data in a global cloud environment. They also offer the reasoning capability to analyze digital manufacturing data for making intelligent decisions.
It is critical in manufacturing to capture and share product manufacturability knowledge across all sites in a global manufacturing enterprise, to enhance competitiveness. Ontologies can make this knowledge shareable more easily.
With the help of AI, including AI based on Large Language Models, the utilization of ontologies supports decision-making in industrial projects, such as preventive maintenance of manufacturing systems, diagnosis and prognostics, cost estimation, etc.
In manufacturing, a process plan for a product comprises manufacturing operations, their sequences, and manufacturing resources for implementing the operations. An ontology can semantically represent this knowledge, avoiding interoperability and misinterpretation issues.
Therefore, paying attention to the architecture and improvements of manufacturing ontologies leads to more efficient, effective, and competitive manufacturing processes.
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