Publicação
Integration of machine learning models in a microservices architecture
| Resumo: | Achieving Zero Defect Manufacturing in the evolving landscape of Industry 4.0 requires advanced, scalable architectures that support proactive quality management and real-time defect detection. This thesis introduces a ZDM-focused microservices architecture designed to enhance modularity, resilience, and scalability within industrial manufacturing environments. By integrating Cyber-Physical Systems and Digital Twins, the proposed architecture facilitates continuous monitoring, dynamic data flow, and predictive analyt- ics, aligning with RAMI 4.0 standards to ensure seamless interoperability across systems. Emphasizing communication-driven design, the architecture leverages distributed microservices and specialized communication brokers to create a flexible, event-driven system. This enables efficient handling of high data volumes, real-time quality insights, and early anomaly detection. Through a structured evaluation of core architectural components, including orchestration, choreography, and communication brokers, this work establishes a foundation for ZDM implementations adaptable to various industrial settings. The architecture’s deployment in a real-world manufacturing case demonstrates its practical benefits, illustrating how modular, scalable systems can drive operational improvements and defect reduction. Contributing to the broader Industry 4.0 framework, this work provides a blueprint for future ZDM solutions that prioritize sustainability, adaptability, and enhanced product quality in complex manufacturing ecosystems. Keywords: Microservices architecture, Message brokers, Industry 4.0 |
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| Autores principais: | Ibrahim, Ahmed Gamal Ali Ali |
| Assunto: | Microservices architecture Message broker Industry 4.0 |
| Ano: | 2024 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Bragança |
| Idioma: | inglês |
| Origem: | Biblioteca Digital do IPB |
| Resumo: | Achieving Zero Defect Manufacturing in the evolving landscape of Industry 4.0 requires advanced, scalable architectures that support proactive quality management and real-time defect detection. This thesis introduces a ZDM-focused microservices architecture designed to enhance modularity, resilience, and scalability within industrial manufacturing environments. By integrating Cyber-Physical Systems and Digital Twins, the proposed architecture facilitates continuous monitoring, dynamic data flow, and predictive analyt- ics, aligning with RAMI 4.0 standards to ensure seamless interoperability across systems. Emphasizing communication-driven design, the architecture leverages distributed microservices and specialized communication brokers to create a flexible, event-driven system. This enables efficient handling of high data volumes, real-time quality insights, and early anomaly detection. Through a structured evaluation of core architectural components, including orchestration, choreography, and communication brokers, this work establishes a foundation for ZDM implementations adaptable to various industrial settings. The architecture’s deployment in a real-world manufacturing case demonstrates its practical benefits, illustrating how modular, scalable systems can drive operational improvements and defect reduction. Contributing to the broader Industry 4.0 framework, this work provides a blueprint for future ZDM solutions that prioritize sustainability, adaptability, and enhanced product quality in complex manufacturing ecosystems. Keywords: Microservices architecture, Message brokers, Industry 4.0 |
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