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Interoperability Flagship: Optimising supply chain environmental data flow with AI/ML

Interoperability Flagship: Optimising supply chain environmental data flow with AI/ML
互操作性旗舰:利用人工智能/机器学习优化供应链环境数据流
批准号:
10056911
负责人:
金额:
$95.47万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --

项目摘要

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中文摘要
翻译
该互操作性旗舰项目将开发一个创新的人工智能/机器学习驱动的互操作性层,作为Digital Catapult公司数字供应链创新中心(DSCH)的核心能力。该项目旨在加速和自动化供应链上的信息流,以优化产品和资金的流动,加强英国制造商的弹性和可持续性。我们的目标是通过克服信息流的主要障碍之一来实现这一目标:互操作性不足,即系统无法为交换、解释和使用数据来改进决策而无缝通信。对于这个项目,我们专注于优化工程和碳数据流,为网络铁路的transennine路线升级使用财政部资助的共享数字碳架构计划作为核心框架和数字工具进行集成。该项目将汇集来自整个行业的主要利益相关者:网络铁路,Costain,莫特麦克唐纳,宾利系统,数字弹射器和国家物理实验室。我们将使用尖端的AI/ML技术,结合基础数据/语义模型,推断和指导系统接口之间的连接,并在供应链系统之间动态地产生互操作性。这将产生一种新的互操作性方法,使供应链能够迅速实现数字化、优化和持续,以满足英国范围内的目标,如气候、生产力、弹性和政策监测。参与其中的企业的主要成果将是将其公共数据环境(CDE)转换为连接的数据环境。CDE是一个基于云的空间,存储来自建筑项目的信息,并允许参与者访问。然而,这些数据往往是低质量的、不完整的和过时的。今天,核实一个项目的排放量至少需要10周的时间,而我们的目标是在10秒内完成。我们将通过从商业模式和技术解决方案两个角度解决挑战来实现这一目标。首先查看业务需求以解锁碳和工程数据流,并设计激励措施和业务模型以支持这些需求。然后,我们将开发算法和语义模型,为这个用例创建互操作性层,然后可以扩展到我们在项目期间排队的各种其他用例(例如跨合作伙伴计划和更广泛的数字供应链中心生态系统的应用程序)。
英文摘要
This Interoperability Flagship project will develop an innovative Artificial Intelligence / Machine Learning powered interoperability layer as a core capability of Digital Catapult's Digital Supply Chain Innovation Hub (DSCH).The project aims to speed up and automate the flow of information across supply chains to optimise the flows of products and money, strengthening the resilience and sustainability of UK manufacturers. We aim to do this by overcoming one of the key blockers of information flow: Inadequate interoperability where systems are not able to communicate seamlessly for the purpose of exchanging, interpreting and using data to improve decision making.For this project we are focused on optimising engineering and carbon data flows for Network Rail's Transpennine Route Upgrade using the Treasury funded Shared Digital Carbon Architecture programme as the core framework and digital tools to integrate with. The project will bring together leading stakeholders from across industry: Network Rail, Costain, Mott MacDonald, Bentley Systems, Digital Catapult, and National Physical Laboratory.We will use cutting edge AI/ML techniques, in combination with foundational data/semantic models, to infer and guide connections between system interfaces and generate interoperability dynamically across supply chain systems. This would then result in a new approach to interoperability that will enable the supply chain to be digitalised, optimised and sustained quickly enough to meet UK wide goals such as climate, productivity, resilience and monitoring of policy.The principal outcome for participating businesses will be to transform their common data environments (CDE) into connected data environments. A CDE is a cloud-based space where information from construction projects is stored and access is permissioned to participants. However, the data is often low quality, incomplete and out of date. Today, to verify the emissions of a project can take a minimum of 10 weeks - if at all - whereas we aim to be able to deliver it in 10 seconds.We will achieve this by addressing the challenge from both the business model and technology solution angles. First looking at the business requirements to unlock carbon and engineering data flow, and designing the incentives and business model to support those requirements. Then we will develop the algorithms and semantic models to create the interoperability layer for this use case and can then be expanded to a variety of others that we line up during the project (such as the application across partner programmes and the broader Digital Supply Chain Hub ecosystem).
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