NARRATE: Regenerative Resilient Smart Manufacturing Networks
NARRATE: Regenerative Resilient Smart Manufacturing Networks
批准号:
10108479
负责人:
金额:
$41.55万
依托单位:
依托单位国家:
英国
项目类别:
EU-Funded
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
制造和物流公司经常受到不可预见的事件的影响,这些事件会破坏供应链,导致生产放缓、产量减少和成本增加,从而难以满足客户需求。为了减轻这些风险,制造商必须在整个价值链中建立弹性。NARRATE将使用人工智能、数字孪生和物联网技术开发一种复杂的工具,允许端到端可见性和对供应链运营的控制,以监控和预测潜在的中断,使供应链能够提高弹性。智能制造保管员(IMC)将利用来自各种生产来源的数据来实现主动决策,并充当供应链网络的神经中枢,提供智能生产过程和物流的实时监控和协调。将集成集成管理中心集成到供应链中,将使其运营演变为智能制造网络(SMN):一个连接的、自协调的生态系统,端到端与可编程的制造即服务功能相连,可以承受中断。数字孪生将提供可靠的模型来表示SMN的生产和运行数据,以解锁更深层次的IMC智能。收集的数据将训练机器学习模型来预测潜在的中断,如自然灾害或延迟发货。人工智能算法将分析数据,并在仪表板上提供实时报告和可视化。IMC和Digital Twin的互动将产生强大的洞察力和自适应能力,支持SMN在人类监督下发展,通过在多个外部合作伙伴之间切换服务来应对风险和中断,并在整个生产过程中提高能源效率、产品循环性和环境可持续性。将通过在相当不同的工业部门的实际生产环境中测试综合管理能力来评价叙事的有效性。
英文摘要
Manufacturing and logistics companies are subject to unforeseen events that disrupt the supply chain, causing production slowdowns, reduced output, and increased costs, making it difficult to meet customer demand. To mitigate these risks, manufacturers must build resilience across entire value chains. NARRATE will develop a sophisticated tool using AI, Digital Twin, and IoT technologies allowing end-to-end visibility and control over supply chain operations to monitor and predict potential disruptions, enabling supply chains to achieve improved resilience. The Intelligent Manufacturing Custodian (IMC) will leverage data from various production sources to enable proactive decision-making and act as a nerve centre for a supply-chain network, providing real-time monitoring and coordination of intelligent production processes and logistics. Integrating an IMC into a supply-chain will evolve its operations into Smart Manufacturing Network (SMN): a connected and self-orchestrated ecosystem linked end-to-end with programmable Manufacturing-as a-Service capabilities that can withstand disruptions. A Digital Twin will provide a reliable model to represent production and operational data of an SMN to unlock deeper IMC intelligence. Collected data will train machine learning models to predict potential disruptions, such as natural disasters or delayed shipments. AI algorithms will analyse the data and provide real-time reporting and visualization on a dashboard. The IMC and Digital Twin interaction will generate powerful insights and self-adapting abilities that support an SMN to evolve under human supervision by switching services between multiple external partners to respond to risks and disruptions and improve energy efficiency, product circularity and environmental sustainability across the entire production process. The effectiveness of NARRATE will be evaluated by testing the IMC in real production environments in quite diverse industry sectors.
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