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Dynamic scheduling following RAMI4.0 reference architecture
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Resumo(s)
A Indústria 4.0 transformou a indústria de manufactura de sistemas lineares para sistemas
altamente interconectados, através da digitalização e integração de tecnologias avançadas.
Esta transformação resultou num aumento da eficiência, na redução de desperdícios e na
possibilidade de produzir produtos personalizados em escala. No entanto, a integração
destas tecnologias apresenta desafios, como a interoperabilidade fluida, a gestão de grandes
quantidades de dados gerados por dispositivos IoT, cibersegurança e o desenvolvimento de
novas competências da força de trabalho.
Outro desafio da indústria tem sido a alocação de tarefas para uma otimização do
processo de produção. Esse desafio é ainda mais acentuado na I4.0, uma vez que os métodos
tradicionais têm dificuldade em lidar com a natureza dinâmica e imprevisível da manufactura
moderna. Esta tese propõe um sistema para a execução e monitorização dinâmica de tarefas,
seguindo as práticas RAMI 4.0. O sistema inclui um algoritmo para uma alocação eficiente de
tarefas, uma camada middleware para a comunicação e troca de dados, e Asset
Administration Shells (AAS) para fornecer dados detalhados sobre capacidades, requisitos e
tempos de processamento. A Base de Dados AAS consolida esta informação e encaminha-a
para o Escalonador, que depois gera cronogramas de produção otimizados, aumentando a
eficiência, flexibilidade e adaptabilidade nas operações de manufatura. Esta tese pretende
contribuir para o conhecimento sobre programação dinâmica na Indústria 4.0 e fornecer uma
solução prática para que os fabricantes possam navegar pelas complexidades dos processos
de manufatura modernos.
Industry 4.0, the digitization and integration of advanced technologies, has transformed the manufacturing industry from linear to highly interconnected systems. This has led to increased efficiency, reduced waste, and customized products at scale. However, the integration of these technologies presents challenges such as seamless interoperability, managing vast amounts of data generated by IoT devices, cybersecurity, and workforce upskilling. Another challenge in the industry has been the allocation of tasks for optimizing the production process. This challenge is even more pronounced in Industry 4.0, as traditional methods struggle to cope with the dynamic and unpredictable nature of modern manufacturing. This thesis proposes a system for dynamically executing and monitoring tasks, following RAMI 4.0 practices. The system includes an algorithm for efficient task allocation, a middleware layer for communication and data exchange, and Asset Administration Shells (AAS) for detailed data on capabilities, requirements, and processing times. The AAS Database consolidates this information,forwards it to the Scheduler that then generates optimized production schedules, enhancing efficiency, flexibility, and adaptability in manufacturing operations. This thesis aims to contribute to the knowledge on dynamic scheduling within Industry 4.0 and provide a practical solution for manufacturers to navigate the complexities of modern manufacturing processes.
Industry 4.0, the digitization and integration of advanced technologies, has transformed the manufacturing industry from linear to highly interconnected systems. This has led to increased efficiency, reduced waste, and customized products at scale. However, the integration of these technologies presents challenges such as seamless interoperability, managing vast amounts of data generated by IoT devices, cybersecurity, and workforce upskilling. Another challenge in the industry has been the allocation of tasks for optimizing the production process. This challenge is even more pronounced in Industry 4.0, as traditional methods struggle to cope with the dynamic and unpredictable nature of modern manufacturing. This thesis proposes a system for dynamically executing and monitoring tasks, following RAMI 4.0 practices. The system includes an algorithm for efficient task allocation, a middleware layer for communication and data exchange, and Asset Administration Shells (AAS) for detailed data on capabilities, requirements, and processing times. The AAS Database consolidates this information,forwards it to the Scheduler that then generates optimized production schedules, enhancing efficiency, flexibility, and adaptability in manufacturing operations. This thesis aims to contribute to the knowledge on dynamic scheduling within Industry 4.0 and provide a practical solution for manufacturers to navigate the complexities of modern manufacturing processes.
Descrição
Palavras-chave
Scheduling Industry 4.0 Asset Administration Shells Optimized production schedules RAMI 4.0