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Circular4.0: Data Driven Intelligence for a Circular Economy

Circular4.0: Data Driven Intelligence for a Circular Economy
Circular4.0:数据驱动的智能循环经济
批准号:
EP/R032041/1
负责人:
Fiona Charnley
金额:
$98.83万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2019
资助国家:
英国
项目状态:
已结题
起止时间:
2019 至 --

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中文摘要
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英文摘要
Circular approaches to design, manufacture and services are proposed as one of the most significant opportunities to radically re-think how we use and re-use finite resources. Pairing the digital revolution with the principles of a Circular Economy (CE) has the potential to radically transform the industrial landscape and its relationship to materials and finite resources, thus unlocking additional value for the manufacturing sector. Despite meaningful success by a handful of manufacturers to move towards more sustainable practices through the use of data-driven intelligence, it is unclear which CE strategy is the most valuable for a business and at what time in a products lifecycle it should be implemented. As such, this research aims to identify how data from products in use can inform intelligent decisions surrounding the implementation of Circular Economy strategies so as to accelerate the implementation of circular approaches to resource use within UK manufacturing.Multiple research efforts and best practice examples have shown that a transition towards a Circular Economy can bring about lasting benefits from a more innovative, resilient and productive economy. This is particularly prevalent for manufacturing as it offers one of the biggest potentials for economic and environmental impact of any sector. It is estimated that materials savings alone in the European Union could amount to USD 630 billion. Digital technology is rapidly becoming a key enabler for unlocking the value from Circular Economy strategies with an estimated 10 billion physical objects with embedded information technology already in existence today and a predicted 50 billion in use by 2020. For the manufacturing sector, the ability to monitor and manage objects in the physical world electronically through data-driven decision-making changes the way that value is created. The capture and analysis of data streams between manufacturing, product and user is already enabling organisations to decouple manufacturing growth from resource consumption through new service offerings, providing customers with added value such as financial savings and safety improvement, and enabling organisations to shift their business model from selling to leasing. This shift in ownership, enabled through access to the right data, brings about a need for manufacturers to design products that last and to integrate processes such as remanufacturing to enable materials and resources to be cycled as many times as possible resulting in significant environmental savings, job creation and up-skilling associated with the development of new processes. Through harnessing digital technological advances to inform decisions on Circular Economy strategies, this research has the opportunity to radically transform UK manufacturing and enable the sector to capture significant value from a Circular Economy that is currently being lost.The originality of this research lies in using data-driven intelligence to optimise the selection of CE strategies for products and the timings of intervention in the product lifecycle. This challenging three year project will bring together an internationally renowned team of experts in Circular Innovation, Manufacturing Informatics and Information Theory from Cranfield University and University of Sheffield drawing on leading-edge strengths of the host institutions and international connections with research communities, companies, business intermediaries and governance at national and international scales. The research team will partner with key players across the manufacturing sector, capable of initiating system level change, to develop novel methods for acquiring and integrating new data streams, uncovering exciting opportunities for new value creation within manufacturing organisations and enabling informed circular interventions surrounding the manufacture and use of products.
期刊论文(10)
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科研奖励(0)
会议论文
DOI: 10.1515/9783110723373-011
发表时间: 2023
期刊:
影响因子: --
作者: [Haines-Gadd M]
通讯作者: Haines-Gadd M
DOI: 10.3390/su14084589
发表时间: 2022
期刊: Sustainability
影响因子: 3.9
作者: [Charnley F]
通讯作者: Charnley F
DOI: 10.1016/j.clscn.2022.100087
发表时间: 2022-11
期刊: Cleaner Logistics and Supply Chain
影响因子: --
作者: [O. Okorie;Jennifer D. Russell;Yifan Jin;C. Turner;Yongjing Wang;Fiona Charnley]
通讯作者: O. Okorie;Jennifer D. Russell;Yifan Jin;C. Turner;Yongjing Wang;Fiona Charnley
DOI: 10.3390/su11123379
发表时间: 2019-06-02
期刊: SUSTAINABILITY
影响因子: 3.9
作者: [Charnley, Fiona, Tiwari, Divya, Tiwari, Ashutosh]
通讯作者: Tiwari, Ashutosh
7
    UKRI National Interdisciplinary Circular Economy Hub
    • 批准号:
      EP/V029746/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $468.03万
    • 财政年份:
      2021
    • 负责人:
      Fiona Charnley
    • 依托单位:
    Circular4.0: Data Driven Intelligence for a Circular Economy
    • 批准号:
      EP/R032041/2
    • 项目类别:
      Research Grant
    • 资助金额:
      $92.75万
    • 财政年份:
      2019
    • 负责人:
      Fiona Charnley
    • 依托单位:
    RECODE Consumer Goods, Big Data and Re-Distributed Manufacturing
    • 批准号:
      EP/M017567/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $59.56万
    • 财政年份:
      2015
    • 负责人:
      Fiona Charnley
    • 依托单位:
    国内基金
    海外基金
    Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
    Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
    Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
    • 批准号:
      --
    • 项目类别:
      --
    • 资助金额:
      40万元
    • 批准年份:
      2020
    • 负责人:
      Vikrant Gupta
    • 依托单位:
    基于Linked Open Data的Web服务语义互操作关键技术
    • 批准号:
      61373035
    • 项目类别:
      面上项目
    • 资助金额:
      77.0万元
    • 批准年份:
      2013
    • 负责人:
      冯志勇
    • 依托单位: