2022
DOI: 10.1016/j.apenergy.2022.119986
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Digital twin and big data-driven sustainable smart manufacturing based on information management systems for energy-intensive industries

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Cited by 114 publications
(26 citation statements)
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“…Linking DTs with big data technologies offers potential in terms of data collection, prediction, and analysis along the product life cycle. In Ma et al, (2022), a framework for the integration of big data in DTs is presented to enable sustainable manufacturing. The use of DT in combination with AI increases the potential benefits, for example to enable the automated early identification of faults or damage (Argyroudis et al, 2022) or to improve the selection of recyclable materials.…”
Section: Main Benefits Of Digital Twins For More Sustainabilitymentioning
confidence: 99%
“…Linking DTs with big data technologies offers potential in terms of data collection, prediction, and analysis along the product life cycle. In Ma et al, (2022), a framework for the integration of big data in DTs is presented to enable sustainable manufacturing. The use of DT in combination with AI increases the potential benefits, for example to enable the automated early identification of faults or damage (Argyroudis et al, 2022) or to improve the selection of recyclable materials.…”
Section: Main Benefits Of Digital Twins For More Sustainabilitymentioning
confidence: 99%
“…In the manufacturing industry, digital twin technology can be used to simulate the energy consumption of a manufacturing facility and identify opportunities for energy savings. It allows for testing of different configurations of equipment and process, evaluating the performance and optimizing the energy usage before making any changes in the real facility [103]. On the other hand, in smart cities, digital twin technology can be used to simulate the energy consumption of a city and identify opportunities for energy savings.…”
Section: Energy Management Using Digital Twin Technologymentioning
confidence: 99%
“…In addition, it can optimize resource use during the construction, maintenance, and end-of-life phases. An example is the use of digital twins 6 . This is a virtual representation of an object or system that spans its lifecycle, is updated from real-time data, and uses simulation, machine learning and attendant reasoning to help decision-making, also about materialefficiency 7 .…”
Section: Digital Technologiesmentioning
confidence: 99%