Project "ARCA" - Automated Real-Time Classification in Aerospace Maintenance, Repair, Overhaul & Logistics market

“ARCA”项目 - 航空航天维护、修理、大修自动实时分类

• 批准号: 710473
• 金额: $ 12.2万
• 依托单位: WARWICK ANALYTICAL SOFTWARE LIMITED
• 依托单位国家: 英国
• 项目类别: GRD Proof of Concept
• 财政年份: 2014
• 资助国家: 英国
• 起止时间: 2014 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=710473
• 关键词: Project; ARCA; Automated; Real; Time

There are significant challenges and costs in Maintenance, Repair and Overhaul & Logistics(MRO&L) in terms of identifying and resolving issues quickly leading to significant cost,delays and ultimately safety. This is due to a number of factors: increasing complexity ofsystems, interrelatedness of distinct issues and nature of the data collected which is big, dirtyand disparate. Getting to the root cause of an issue can save time and money and can havesignificant impact for companies involved.Warwick Analytics has been approached by several companies to look at No Fault Foundissues in the aerospace. WA has had some success but has encountered particular problemswith data which, whilst applicable to other industries, are particularly problematic in theaerospace industry.MRO&L data is generally collected manually either written or through computer forms.However the data are often semantically incorrect due to different interpretations of aproblem. Whilst intentions are good, it can make it difficult to get to the root cause of issues.Commonly, the data has to be reinterpreted/classified by hand so that it can then be used infurther.This Proof of Concept project will create a new specialist concept tool to convert syntacticallycorrect but semantically incorrect data to help resolve the root cause of the issue in real-time,ultimately leading to cost effective solutions in MRO&L to enable predictive and preventativemaintenance. This will apply to NFFs which are generally the most challenging issues to rootcause.

在快速识别和解决导致重大成本、延误和最终安全的问题方面，维护、维修、大修和物流（MRO&L）面临着巨大的挑战和成本。这是由于许多因素造成的：系统的复杂性增加，不同问题的相互关联性，以及收集的数据的性质，这些数据是大的，脏的和不同的。找到问题的根本原因可以节省时间和金钱，并对相关公司产生重大影响。有几家公司与沃里克分析公司接洽，研究航空航天领域的无故障发现问题。WA取得了一些成功，但在数据方面遇到了一些特别的问题，这些问题虽然适用于其他行业，但在航空航天行业尤其成问题。MRO&L数据通常是手工或书面或通过计算机表格收集的。然而，由于对问题的不同解释，数据往往在语义上不正确。虽然意图是好的，但它可能会使我们很难找到问题的根本原因。通常，数据必须手工重新解释/分类，以便可以进一步使用。这个概念验证项目将创建一个新的专业概念工具来转换语法正确但语义不正确的数据，以帮助实时解决问题的根本原因，最终在MRO&L中产生具有成本效益的解决方案，从而实现预测性和预防性维护。这将适用于nff，这通常是最具挑战性的根本原因问题。