Integrating information technology (IT) and operational technology (OT) in the manufacturing ecosystem is crucial for improving productivity, efficiency, and situational awareness. However, integrating various IT/OT systems is often time-consuming and expensive. Semantic integration resolves this by unifying data from heterogeneous sources while preserving the contextual meaning of each source. The success of semantic integration requires robust ontologies that describe objects, processes, and relationships for knowledge representation, system integration, and semantic interoperability. Despite the significance of ontologies in many industrial domains, a scientifically defined ontology for the motor manufacturing process is in demand. This research addressed this gap by applying the top-down approach with 5M (manpower, machine, method, measurement, and material) methodology to develop a generic motor winding process ontology systematically. Encoded in the Terse RDF Triple Language (TTL), the developed ontology systematically addressed the needs of diverse job roles by incorporating fundamental aspects such as motor types, winding techniques, and thermal classes. The ontology consisted of a clear definition of core classes and their relationships, and outlined the major factors influencing the motor winding process. Finally, validation experiments confirmed the robustness of the ontology through syntax validation, logical validation using “HermiT” reasoning, domain compatibility assessments via competency questions, and SPARQL query execution outputs. The results confirmed the robustness of the ontology and its applicability, offering a framework for semantic interoperability and knowledge representation in the motor winding process.

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