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A framework for man...
A framework for manufacturing system reconfiguration and optimisation utilising digital twins and modular artificial intelligence
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- Mo, Fan (författare)
- Univ Nottingham, Inst Adv Mfg, Nottingham NG8 1BB, Notts, England.
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- Rehman, Hamood Ur (författare)
- Univ Nottingham, Inst Adv Mfg, Nottingham NG8 1BB, Notts, England.;TQC Automation Ltd, Nottingham NG3 2NJ, Notts, England.
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- Monetti, Fabio Marco, MSc, 1991- (författare)
- KTH,Produktionsutveckling
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- Chaplin, Jack C. (författare)
- Univ Nottingham, Inst Adv Mfg, Nottingham NG8 1BB, Notts, England.
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- Sanderson, David (författare)
- Univ Nottingham, Inst Adv Mfg, Nottingham NG8 1BB, Notts, England.
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- Popov, Atanas (författare)
- Univ Nottingham, Inst Adv Mfg, Nottingham NG8 1BB, Notts, England.
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- Maffei, Antonio, 1982- (författare)
- KTH,Produktionsutveckling
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- Ratchev, Svetan (författare)
- Univ Nottingham, Inst Adv Mfg, Nottingham NG8 1BB, Notts, England.
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Univ Nottingham, Inst Adv Mfg, Nottingham NG8 1BB, Notts, England Univ Nottingham, Inst Adv Mfg, Nottingham NG8 1BB, Notts, England.;TQC Automation Ltd, Nottingham NG3 2NJ, Notts, England. (creator_code:org_t)
- Elsevier BV, 2023
- 2023
- Engelska.
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Ingår i: Robotics and Computer-Integrated Manufacturing. - : Elsevier BV. - 0736-5845 .- 1879-2537. ; 82, s. 102524-
- Relaterad länk:
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https://doi.org/10.1...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Digital twins and artificial intelligence have shown promise for improving the robustness, responsiveness, and productivity of industrial systems. However, traditional digital twin approaches are often only employed to augment single, static systems to optimise a particular process. This article presents a paradigm for combining digital twins and modular artificial intelligence algorithms to dynamically reconfigure manufacturing systems, including the layout, process parameters, and operation times of numerous assets to allow system decision -making in response to changing customer or market needs. A knowledge graph has been used as the enabler for this system-level decision-making. A simulation environment has been constructed to replicate the manufacturing process, with the example here of an industrial robotic manufacturing cell. The simulation environment is connected to a data pipeline and an application programming interface to assist the integration of multiple artificial intelligence methods. These methods are used to improve system decision-making and optimise the configuration of a manufacturing system to maximise user-selectable key performance indicators. In contrast to previous research, this framework incorporates artificial intelligence for decision -making and production line optimisation to provide a framework that can be used for a wide variety of manufacturing applications. The framework has been applied and validated in a real use case, with the automatic reconfiguration resulting in a process time improvement of approximately 10%.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Robotteknik och automation (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Robotics (hsv//eng)
Nyckelord
- Reconfigurable manufacturing system
- Modular artificial intelligence
- Digital twin
- Process simulation
- Knowledge graphs
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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