ORCID Profile
0000-0003-4870-3429
Current Organisation
Deakin University
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Publisher: FapUNIFESP (SciELO)
Date: 2020
Abstract: Abstract: The recent development of advanced manufacturing concepts brings new challenges for developing countries in order to prepare their workforce and industries for local and global markets. To explore and disseminate advanced manufacturing concepts, the first autonomous advanced manufacturing cell developed in Brazil as a result of a partnership between global and local companies and academia was designed and evaluated. This paper aims to describe the advanced manufacturing cell, the equipment composing the infrastructure, and the network topology and equipment that could deal with the heterogeneity of equipment and protocol. Moreover, the behavior of the Open Platform Communications Unified Architecture (OPC UA) communication framework (and related protocols) as the integration element between the equipment composing the cell was evaluated. The results indicated that the OPC UA communication framework promotes a low traffic overhead and can also be used to carry data from the traditional protocols in their fields without restrictions that could hinder production. The paper also discusses how the exchange of data occurred between the equipment used in the production and the control systems via the protocol studied. The OPC UA communication framework protocols presented a messaging structure and data transport characteristics that satisfy the integration needs between equipment of several manufacturers that composed an autonomous cell of advanced manufacturing. This paper also presents some key challenges to integrating all equipment not addressed by the OPC UA reference model.
Publisher: Elsevier BV
Date: 02-2023
Publisher: IEEE
Date: 24-10-2022
Publisher: FapUNIFESP (SciELO)
Date: 2020
Abstract: Abstract: Advanced Manufacturing or Industry 4.0 concepts bring new advances and challenges to current industrial processes. Such concepts are not always well understood and their results in terms of production performance may not be clear. This work proposes a comparison between a traditional manufacturing process and an advanced manufacturing process, both modelled by a multiagent society. In the traditional manufacturing simulation, the agents follow the defined times of each process, including the maintenance times. In the advanced manufacturing simulation, the decision about when to stop a piece of equipment for maintenance is defined by the agent according to data received from sensors and the definitions of the process. The results indicate a significant improvement in equipment usage and consequently higher production in the same time interval. The process simulation clearly indicates that the application of advanced manufacturing concepts in industry is relevant in order to increase the efficiency of production processes. Among the main concepts introduced in advanced manufacturing models are the Internet of Things (IoT), Cyber-Physical Systems (CPSs), and Artificial Intelligence (AI). The models generated are computationally simulated using an agent-based simulation method from the software AnyLogic. The results obtained should contribute to encouraging small and medium sized enterprises to adopt the concepts of Industry 4.0 in their businesses.
Publisher: Springer International Publishing
Date: 2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2022
Publisher: IEEE
Date: 06-2019
Publisher: MDPI AG
Date: 11-01-2019
DOI: 10.3390/S19020276
Abstract: The smart management of freshwater for precision irrigation in agriculture is essential for increasing crop yield and decreasing costs, while contributing to environmental sustainability. The intense use of technologies offers a means for providing the exact amount of water needed by plants. The Internet of Things (IoT) is the natural choice for smart water management applications, even though the integration of different technologies required for making it work seamlessly in practice is still not fully accomplished. The SWAMP project develops an IoT-based smart water management platform for precision irrigation in agriculture with a hands-on approach based on four pilots in Brazil and Europe. This paper presents the SWAMP architecture, platform, and system deployments that highlight the replicability of the platform, and, as scalability is a major concern for IoT applications, it includes a performance analysis of FIWARE components used in the Platform. Results show that it is able to provide adequate performance for the SWAMP pilots, but requires specially designed configurations and the re-engineering of some components to provide higher scalability using less computational resources.
Start Date: 2017
End Date: 2020
Funder: European Commission
View Funded Activity