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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 --

项目摘要

项目成果

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中文摘要
翻译
设计、制造和服务的循环方法被认为是从根本上重新思考我们如何使用和再利用有限资源的最重要机会之一。将数字革命与循环经济(CE)原则相结合,有可能从根本上改变工业格局及其与材料和有限资源的关系,从而为制造业释放额外价值。尽管少数制造商通过使用数据驱动的智能,在转向更可持续的实践方面取得了有意义的成功,但目前尚不清楚哪种CE战略对企业最有价值,以及应该在产品生命周期的什么时候实施。因此,本研究旨在确定使用中的产品数据如何为围绕循环经济战略的实施提供明智的决策,从而加快英国制造业资源利用循环方法的实施。多项研究工作和最佳实践实例表明,向循环经济过渡可以从更具创新性、弹性和生产力的经济中带来持久效益。这在制造业中尤为普遍,因为它是所有行业中对经济和环境影响最大的行业之一。据估计,仅在欧盟节省的材料就可达6300亿美元。数字技术正迅速成为释放循环经济战略价值的关键推动因素,据估计,目前已有100亿个嵌入信息技术的实物存在,预计到2020年将有500亿个实物投入使用。对于制造业来说,通过数据驱动的决策以电子方式监控和管理物理世界中的对象的能力改变了价值创造的方式。对制造、产品和用户之间的数据流的捕获和分析,已经使企业能够通过新的服务产品,将制造增长与资源消耗脱钩,为客户提供财务节约和安全改进等附加价值,并使企业能够将其业务模式从销售转变为租赁。通过访问正确的数据,这种所有权的转变使得制造商需要设计耐用的产品,并整合再制造等流程,使材料和资源能够尽可能多地循环使用,从而显著节约环境,创造就业机会,并提高与新工艺开发相关的技能。通过利用数字技术进步为循环经济战略决策提供信息,这项研究有机会从根本上改变英国制造业,并使该行业能够从循环经济中获得目前正在失去的重要价值。本研究的独创性在于使用数据驱动的智能来优化产品的CE策略选择和产品生命周期干预的时机。这个具有挑战性的为期三年的项目将汇集来自克兰菲尔德大学和谢菲尔德大学的循环创新,制造信息学和信息论方面的国际知名专家团队,利用主办机构的领先优势以及与研究团体,公司,商业中介机构和国家和国际规模的治理的国际联系。研究团队将与制造业的主要参与者合作,能够启动系统级变革,开发获取和集成新数据流的新方法,在制造组织中发现令人兴奋的新价值创造机会,并在产品的制造和使用中实现知情的循环干预。
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)
专著(0)
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
共 7 条
    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: