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: 720611
• 金额: $ 22.85万
• 依托单位: WARWICK ANALYTICAL SOFTWARE LIMITED
• 依托单位国家: 英国
• 项目类别: GRD Development of Prototype
• 财政年份: 2015
• 资助国家: 英国
• 起止时间: 2015 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=720611
• 关键词: Project; ARCA; Automated; Real; Time

There are significant challenges and costs in aerospace Maintenance, Repair and Overhaul &Logistics (MRO&L) in terms of identifying, resolving and preventing issues quickly leadingto significant cost, delays and ultimately safety. This is due to a number of factors: increasingcomplexity of systems, interrelatedness of distinct issues and challenges with analysing thedata.Warwick Analytics (WA) has been approached by several companies to solve No Fault Foundand other recurrent maintenance issues in the aerospace industry. WA has had some successwith structured data, but has encountered challenges with the dirty, unstructured andheterogeneous data which are unfortunately the norm in the industry.MRO&L data are typically collected manually either written or through computer forms.There are also sensor “Internet of Things” live condition-monitoring and asynchronousdiagnostic data which are collected and typically in disparate formats. Written data are oftensemantically incorrect due to different interpretations and understanding of a problem orsymptom, and sometimes syntactically incorrect too (i.e. mistakes). This can make it difficultto get to the root cause of issues and therefore resolve them or predict/prevent maintenance inthe future. The state of the art is for data to be manually cleaned, reinterpreted and classifiedby hand so that it can then be used. This is a laborious and ultimately flawed process. Linkingit to sensor and diagnostic data is almost impossible by current means.This Development of Prototype project builds on the successful Proof of Concept project tocreate a new industry solution Aerospace Root Cause Analysis (“ARCA”) using ‘real-world’unstructured, dirty, heterogeneous aerospace data to resolve the root causes of issues in realtime,ultimately leading to cost effective solutions in MRO&L to enable effective, automated,predictive and preventative maintenance, tackling one of the largest aggregate costs in theindustry.

在识别、解决和预防快速导致重大成本、延误和最终安全的问题方面，航空航天维护、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：系统日益复杂，不同问题的相互关系以及分析数据的挑战。沃里克分析公司（WA）已经与多家公司接洽，以解决航空航天工业中的无故障发现和其他经常性维护问题。WA在结构化数据方面取得了一些成功，但在处理脏数据、非结构化数据和异构数据方面遇到了挑战，不幸的是，这些数据在行业中是常态。MRO&L数据通常是手工或书面或通过计算机表格收集的。还有传感器“物联网”实时状态监测和异步诊断数据，这些数据通常以不同的格式收集。由于对问题或症状的不同解释和理解，书面数据通常在语义上不正确，有时在语法上也不正确（即错误）。这使得很难找到问题的根本原因，从而解决问题或预测/防止未来的维护。目前的技术水平是手动清理、重新解释和分类数据，以便可以使用。这是一个费力且最终存在缺陷的过程。以目前的方式，将其与传感器和诊断数据连接几乎是不可能的。这个原型开发项目建立在成功的概念验证项目的基础上，创建了一个新的行业解决方案，航空航天根本原因分析（“ARCA”），使用“真实世界”的非结构化、脏的、异构的航空航天数据来实时解决问题的根本原因，最终在MRO&L中提供具有成本效益的解决方案，从而实现有效、自动化、预测性和预防性的维护，解决行业中最大的总成本之一。