Continuous data collection framework for manufacturing industries

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Abstract

The combination of high-performance and quality with cost-effective productivity, realizing reconfigurable, adaptive and evolving factories leading to sustainable manufacturing industries is one of the emerging research challenges in the domain of Internet of Things. So, it is important to define strategies and technical solutions to allow manufacturing process to autonomously react to the changing factors. Continuous data collection from heterogeneous sources and infusion of such data into suitable processes to enable almost realtime reactive systems is emerging research domain. This research work provides a technical framework for continuous data collection in support of the supply network and manufacturing assets optimization based on collaborative production planning. This research work explores its connection to legacy systems, software components and hardware devices to provide information to the different data consumers. The most relevant achievement of this work is the framework to bridge differences among computing systems, devices and networks allowing uniformity for data access by application decoupling data consumers from data sources.

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Ghimire, S., Melo, R., Ferreira, J., Agostinho, C., & Goncalves, R. (2015). Continuous data collection framework for manufacturing industries. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9416, pp. 29–40). Springer Verlag. https://doi.org/10.1007/978-3-319-26138-6_5

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