SCI-FI: SCalable, Intelligent condition monitoring for Foundation Industries

SCI-FI：基础工业的可扩展、智能状态监测

• 批准号: 94008
• 金额: $ 32.25万
• 依托单位: SENSEYE LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=94008
• 关键词: SCI; FI; SCalable; Intelligent; condition

Proper maintenance in domestic Foundation Industries is crucial for everything that matters: productivity, product quality, reliable deliveries and safe working environments. However, in responding to the demands of global competitions, and more recently the effects of COVID-19, management teams have been forced to make difficult decisions to reduce costs.This has resulted in significant cuts to maintenance budgets, which are often seen purely as costs rather than investments. This has resulted in staff reductions, cancellation of third-party maintenance contracts and under-maintained machines with the inevitable consequences for productivity and energy and resource efficiency.There is a pressing need for automated condition monitoring systems that help maintenance teams sustain their effectiveness with fewer resources. Such systems should scale the expertise of the maintenance team, allowing them to manage more machines with fewer people. They should help them optimise machine performance, avoid unplanned downtime and understand the root causes of failures.The SCI-FI project is about adapting a cost-effective approach to automated condition monitoring (CM) and prognostics (PdM), that has been proven in the automotive sector, developed specifically for the needs of metal (Tata) and paper (Smurfit-Kappa) manufacturing. It involves taking techniques, algorithms and user interfaces that were developed for the kinds of discrete, standalone machines common in automotive and adapting them for the coupled machines and processes that predominate in Foundation Industries.This system would help manufacturers in domestic Foundation Industries become more competitive by reducing both CAPEX and OPEX expenditure through more efficient and more effective maintenance strategies.

在国内基金会工业适当的维护是至关重要的一切：生产力，产品质量，可靠的交付和安全的工作环境。然而，为了应对全球竞争的需求，以及最近COVID-19的影响，管理团队被迫做出艰难的决定，以降低成本。这导致了维修预算的大幅削减，维修预算通常被视为纯粹的成本，而不是投资。这导致裁减工作人员、取消第三方维修合同和机器维修不足，从而不可避免地影响到生产力和能源及资源效率。迫切需要自动化状态监测系统，以帮助维护团队以更少的资源维持其有效性。这样的系统应该扩展维护团队的专业知识，使他们能够用更少的人管理更多的机器。他们应该帮助他们优化机器性能，避免计划外停机，并了解故障的根本原因。科幻项目是关于采用一种经济有效的方法来实现自动状态监测（CM）和预测（PdM），这种方法已经在汽车行业得到了验证，专门针对金属（塔塔）和纸张（Smurfit-Kappa）制造的需求而开发。它包括采用为汽车中常见的各种离散、独立机器开发的技术、算法和用户界面，并将其用于基础工业中占主导地位的耦合机器和过程。该系统将通过更高效和更有效的维护策略降低CAPEX和OPEX支出，从而帮助国内Foundation Industries的制造商变得更具竞争力。