A Novel Framework for Intelligent Automation
Autor: | Tiago Coito, João Figueiredo, Miguel S. E. Martins, Susana M. Vieira, João M. C. Sousa, Joaquim L. Viegas, Mariana M. Cunha |
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Přispěvatelé: | ELSEVIER |
Rok vydání: | 2019 |
Předmět: |
0209 industrial biotechnology
Decision support system Computer science Big data Interoperability Cloud computing 02 engineering and technology computer.software_genre Asset (computer security) 020901 industrial engineering & automation Software Resource (project management) 0202 electrical engineering electronic engineering information engineering SCADA Intelligent Automation business.industry 020208 electrical & electronic engineering Industry 4.0 Automation Control and Systems Engineering Middleware (distributed applications) Middleware business Software engineering Manufacturing Execution Systems computer |
Zdroj: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) Agência para a Sociedade do Conhecimento (UMIC)-FCT-Sociedade da Informação instacron:RCAAP |
ISSN: | 2405-8963 |
Popis: | As the industry continues to pursue the reduction of downtimes and increases in the efficiency of resource usage, data appears as a valuable business asset, empowering intelligent automation solutions. In order to deal with current challenges in acquisition and management of data in industrial settings, this paper proposes a framework for intelligent automation. The traditional automation pyramid does not cope with today’s application requirements, as intelligent automation needs to exchange, in realtime, information with all layers of the pyramid, simultaneously. The middleware for intelligent automation provides interoperability through integration software along with cloud functionalities and big data warehousing. The middleware also provides decentralization by connecting to remote decision support systems. This paper presents two real implementation examples of the framework in the wood and the chemical industry. The framework successfully addresses the requirements of key intelligent automation features and data characteristics, supporting the development of support decision systems into automation modules. |
Databáze: | OpenAIRE |
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