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/R032041/2
• 负责人: Fiona Charnley
• 金额: $ 92.75万
• 依托单位: UNIVERSITY OF EXETER
• 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
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FR032041%2F2
• 关键词: Circular4.0; Data; Driven; Intelligence; Circular

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.

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）的原则相结合，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，从而为制造业释放附加价值。尽管少数制造商通过使用数据驱动的智能来实现更可持续的实践取得了有意义的成功，但目前还不清楚哪种CE策略对企业最有价值，以及应该在产品生命周期的什么时候实施。因此，这项研究旨在确定使用中产品的数据如何为围绕实施循环经济战略的明智决策提供信息，以加速英国制造业内资源利用循环方法的实施。多项研究工作和最佳实践示例表明，向循环经济的转型可以从更具创新性、弹性和生产力的经济中带来持久的利益。这在制造业中尤其普遍，因为它是任何部门中经济和环境影响最大的潜力之一。据估计，仅欧洲联盟的材料节省就可达6300亿美元。数字技术正在迅速成为释放循环经济战略价值的关键推动因素，目前估计已有100亿件实物嵌入了信息技术，预计到2020年将有500亿件实物投入使用。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创造价值的方式。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业增长与资源消耗脱钩，为客户提供附加值，如节省资金和提高安全性，并使企业能够将其商业模式从销售转变为租赁。通过访问正确的数据，所有权的这种转变使制造商需要设计持久的产品，并整合再制造等流程，以使材料和资源尽可能多地循环，从而显著节省环境，创造就业机会并提高与新流程开发相关的技能。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，并使该行业能够从目前正在失去的循环经济中获得重要价值。这项研究的独创性在于使用数据驱动的智能来优化产品的CE战略选择和产品生命周期中的干预时机。这个具有挑战性的三年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，制造信息学和信息理论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社区，公司，商业中介机构和国家和国际范围内的治理的国际联系。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，开发新的方法来获取和整合新的数据流，发现制造组织内创造新价值的令人兴奋的机会，并围绕产品的制造和使用进行知情的循环干预。

项目成果

Can Digital Technologies Increase Consumer Acceptance of Circular Business Models? The Case of Second Hand Fashion

数字技术能否提高消费者对循环商业模式的接受度？

• DOI: 10.3390/su14084589
• 发表时间: 2022
• 期刊: Sustainability
• 影响因子: 3.9
• 作者: Charnley F

Circular business models in high value manufacturing: Five industry cases to bridge theory and practice

高价值制造业的循环商业模式：连接理论与实践的五个行业案例

• DOI: 10.1002/bse.2715
• 发表时间: 2021
• 期刊: Business Strategy and the Environment
• 影响因子: 13.4
• 作者: Okorie O

Removing Barriers to Blockchain use in Circular Food Supply Chains: Practitioner Views on Achieving Operational Effectiveness

• DOI: 10.1016/j.clscn.2022.100087
• 发表时间: 2022-11
• 期刊: Cleaner Logistics and Supply Chain
• 作者: O. Okorie;Jennifer D. Russell;Yifan Jin;C. Turner;Yongjing Wang;Fiona Charnley

A Framework to Support a Simulation-Based Understanding of Digitalisation in Remanufacturing Operations

支持基于仿真理解再制造运营中数字化的框架

• 发表时间: 2019
• 作者: Okorie O

Simulation to Enable a Data-Driven Circular Economy

• 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