Online reconfiguration of automatic production line using IEC 61499 FBs combined with MAS and ontology

Wan, Guangxi; Wang, Peng; Nie, Zhenbang; Xue, Lunsheng; Zeng, Peng

doi:10.1109/iecon.2017.8217167

Cited by 3 publications

(1 citation statement)

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“…However, most of the existing systems have to be suspended when reconfiguring because the online reconfiguration may lead the system to disorder and uncertainty. IEC 61499 function blocks combined with MASs and ontology can be used to minimise the leading time of reconfiguration whilst ensuring system stability (Wan et al, 2017).…”

Section: Ontology-based Multiagent System (Mas)mentioning

confidence: 99%

Big data and machine learning: A roadmap towards smart plants

et al. 2022

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Industry 4.0 aims to transform chemical and biochemical processes into intelligent systems via the integration of digital components with the actual physical units involved. This process can be thought of as addition of a central nervous system with a sensing and control monitoring of components and regulating the performance of the individual physical assets (processes, units, etc.) involved. Established technologies central to the digital integrating components are smart sensing, mobile communication, Internet of Things, modelling and simulation, advanced data processing, storage and analysis, advanced process control, artificial intelligence and machine learning, cloud computing, and virtual and augmented reality. An essential element to this transformation is the exploitation of large amounts of historical process data and large volumes of data generated in real-time by smart sensors widely used in industry. Exploitation of the information contained in these data requires the use of advanced machine learning and artificial intelligence technologies integrated with more traditional modelling techniques. The purpose of this paper is twofold: a) to present the state-of-the-art of the aforementioned technologies, and b) to present a strategic plan for their integration toward the goal of an autonomous smart plant capable of self-adaption and self-regulation for short- and long-term production management.

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Section: Ontology-based Multiagent System (Mas)mentioning

confidence: 99%