Governance framework for autonomous and cognitive digital twins in agile supply chains

Kalaboukas, Kostas; Kiritsis, Dimitris; Arampatzis, George

doi:10.1016/j.compind.2023.103857

Cited by 14 publications

(4 citation statements)

References 24 publications

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“…For each potential supplier, inputs and outputs are modeled, and their system behavior is considered throughout the entire supply chain. This can lead to more efficient decisions regarding sustainability in the BoL [40]. Three of the four publications relate to the automotive industry and describe applications at the EoL that relate to returning components to the cycle by providing relevant information along the entire PLC.…”

Section: End-of-life Decision Support To Enable Circular Economy In T...mentioning

confidence: 99%

“…This data from DTs throughout the PLC allows for deriving conclusions about design requirements related to longevity and user behavior (Feedback to Design) [3,13,19,21,29,37]. By considering EoL treatment as well as regional EoL conditions, the product design can be optimized for better reuse, remanufacturing, or recycling (Design for Reuse, Remanufacture, Recycling) [12,17,26,27,39,40]. By finding, analyzing, and evaluating new product configurations, products can be designed for a longer product life [13,14,17,27].…”

Section: Digital Twins For Circular Economy For the Beginning-of-life...mentioning

confidence: 99%

“…This information can be visualized in a DT dashboard, which can be used to make important decisions regarding life cycle assessments at BoL [31]. Sustainability can also be influenced by the choice of suppliers and transport routes [38,40]. In addition, the sustainability of the manufacturing process can be improved by monitoring the status of the system and energy consumption [38,39].…”

Section: Digital Twins For Circular Economy For the Beginning-of-life...mentioning

confidence: 99%

See 2 more Smart Citations

Digital Twins within the Circular Economy: Literature Review and Concept Presentation

Mügge,

Seegrün,

Hoyer

et al. 2024

Sustainability

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Digital twins offer a promising approach to sustainable value creation by providing specific life cycle data and enabling the monitoring and implementation of circular economy strategies throughout the product’s life cycle. By analyzing product, component, and material data, as well as process data, it is possible to create transparency throughout a product’s life cycle, build a data-driven product ecosystem, and establish new business and value creation models, from SMEs to large enterprises. This paper identifies application scenarios, their technological readiness level, and the challenges of digital twins for the circular economy in the manufacturing industry based on a systematic literature review. Gaps such as ensuring a continuous flow of information and taking into account the different levels of digitalization of companies are identified. As a main result, a holistic concept for the scoping of a digital twin for the circular economy is presented. One specific use case for end-of-life decision-making is elaborated upon. It is shown that the circular economy can be supported by digital twin data, especially for the optimal decision on end-of-life vehicles.

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Section: End-of-life Decision Support To Enable Circular Economy In T...mentioning

confidence: 99%

Section: Digital Twins For Circular Economy For the Beginning-of-life...mentioning

confidence: 99%

Section: Digital Twins For Circular Economy For the Beginning-of-life...mentioning

confidence: 99%

See 1 more Smart Citation

Digital Twins within the Circular Economy: Literature Review and Concept Presentation

Mügge,

Seegrün,

Hoyer

et al. 2024

Sustainability

View full text Add to dashboard Cite

show abstract

“…AI's predictive powers improve risk assessment, supporting landscape designers put together for weatherassociated problems and building resilient green spaces. AI-powered solutions make design input and network involvement greater participatory, enhancing social sustainability (Kalaboukas, Kiritsis, & Arampatzis, 2023). This inclusive method fosters duty and improves human-surroundings connections.…”

Section: Integration Of Ai and Sustainabilitymentioning

confidence: 99%

Sustainable Landscape Design and Traditional Villages in Xuzhou, Jiangsu: Low-cost Strategies and Big Data Applications Influencing AI Integration

Wang,

Mayusoh,

Inkuer

2024

J INFORM SYSTEMS ENG

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Big Data usage and Artificial Intelligence (AI) technology combined offer a potential approach to solving challenging problems. AI-driven solutions provide insightful analysis and creative solutions by utilizing the power of big data analytics. With an emphasis on the mediating role of technological literacy and the moderating effect of resource availability, this study investigates the effects of low-cost techniques, the usage of Big Data, and the integration of Artificial Intelligence (AI) on sustainability in landscape design. The purpose of this study is to look at the intricate connections between these factors and how they affect sustainable landscape design methods and results as a whole. A standardized questionnaire was answered by a sample of 458 landscape experts as part of a quantitative approach. Smart PLS (Partial Least Squares), which incorporates evaluations of measurement models, structural models, and mediation and moderation studies, was utilized for data analysis. The study found that using Big Data, implementing low-cost techniques, and incorporating AI all had very favourable effects on sustainability in landscape design. The efficient use of Big Data and AI was found to be mediated by technological literacy, highlighting the importance of this concept in this context. Additionally, resource availability emerged as a critical moderating factor, influencing the strength of these relationships. This research contributes to the field by offering a holistic understanding of the dynamics within sustainable landscape design, emphasizing the importance of integration of AI and utilization of Big Data. It provides practical insights for landscape professionals, informs policy development, and advances educational curricula about AI and Big Data in landscape architecture. The study's limitations include potential response bias due to self-reported data and the cross-sectional design, which restricts the establishment of causal relationships. Additionally, the study focused on professionals, limiting the generalizability of findings to broader community perspectives.

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Planning and building digital twins for smart cities

Channi,

Kumar,

Safdarian

2025

Digital Twins for Smart Cities and Villages

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Governance framework for autonomous and cognitive digital twins in agile supply chains

Cited by 14 publications

References 24 publications

Digital Twins within the Circular Economy: Literature Review and Concept Presentation

Digital Twins within the Circular Economy: Literature Review and Concept Presentation

Sustainable Landscape Design and Traditional Villages in Xuzhou, Jiangsu: Low-cost Strategies and Big Data Applications Influencing AI Integration

Planning and building digital twins for smart cities

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