AUTONOM: Integrated through-life support for high-value systems

AUTONOM：为高价值系统提供集成的终身支持

• 批准号: EP/J011630/1
• 负责人: Andrew Starr
• 金额: $ 118.38万
• 依托单位: CRANFIELD UNIVERSITY
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2013
• 资助国家: 英国
• 起止时间: 2013 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FJ011630%2F1
• 关键词: AUTONOM; Integrated; through; life; support

Summary - This proposal extends research in novel sensing, e-maintenance systems, and decision-making strategies. It is supported by the EPSRC National Centre for Innovative Manufacturing in Through-life Engineering Services. Maintenance of widely-dispersed assets is expensive because it involves widespread inspection, checking and measurement. The integration of sensor-based information in geographically dispersed and less structured environments poses challenges in technology and cost justification. Academic challenges include improvement of embedded sensing, reliable estimation of monitoring parameters, a unified approach to the mathematics and data structures, and a rigorous approach to cost estimation and benefit analysis. The industrial drivers include standardisation, automation, connectivity, and reduction of unit cost. We will build on e-maintenance principles in automated, intelligent maintenance in the context of industrial application: transitions from sensor level to management decision-making. Within the integration architecture we will investigate some research challenges in depth:- Requirements for interchange of maintenance data between fixed and mobile actors, e.g. track-to-train data exchange in rail or aerospace applications.- Automation of monitoring on mobile platforms, and interface with other actors and fixed systems.- New cost modelling tools for complex distributed health monitoring, and especially the value to the business. The novelty lies in the implementation of effective information flows and analysis techniques to support optimisation, and uncertainty based resource scheduling, capturing business "pull" which struggles with lag in the data, and insufficient tools to turn it into information for decision making. Aims and Objectives: The overall aim is to enable improved integration between architectural levels in data-rich environments in automated, intelligent maintenance, responding to business pull and demonstrating value.Objectives:- Identification of the industrial pull for plant and fixed asset management information for maintenance decisions, in the context of technologically rich data sources; i.e. designing the condition based maintenance from the top down.- Transition between architectural levels, from data to information to decision, embedding automatic functionality in appropriate hardware such as wireless platforms and RFID. Transfer between fixed and mobile actors.- Improved data fusion in condition monitoring problems in large data sets.- A demonstrated methodology for mining and optimally reconfiguring maintenance data in the form of a business process.- An estimation tool for cost, value and benefits, with validated application.In a programme directed by industrial "pull", four work packages will cover - Integration, with milestones "Think tank" event report; Definition of data/information and information/decision transitions, illustrated by industrial cases; Strategy document for design; Final report.- Data fusion and mobile platforms, with milestones: Strategy for fusion of multiple unsynchronised sensor data; Case studies of fused multiple unsynchronised sensor data; Strategy for top-down monitoring system design; Reporting/message passing architecture - proof of concept.- Planning and Scheduling Based on Intelligent Reconfigurable Business Processes, with milestones: Identification of a representative set of business processes, in cooperation with the partners; The multi-objective optimisation framework; Validation on a partner's example.- Cost Analysis, with milestones: Identification of best practice cost modelling methods, and cost benefit analysis and value analysis; Development of cost and value models; Framework for estimating costs and benefits of integrated maintenance to the business; Framework for estimating through life costs and benefits of distributed heterogeneous high integrity assets, and Validation of tool set.

摘要-该提案扩展了对新型传感，电子维护系统和决策策略的研究。它得到了EPSRC国家生命工程服务创新制造中心的支持。广泛分散的资产的维护是昂贵的，因为它涉及广泛的检查，检查和测量。将基于传感器的信息整合到地理上分散的、结构化程度较低的环境中，在技术和成本合理性方面提出了挑战。学术上的挑战包括改进嵌入式传感、可靠地估计监测参数、统一的数学和数据结构方法，以及严格的成本估计和效益分析方法。工业驱动因素包括标准化、自动化、连接性和单位成本的降低。我们将在工业应用背景下建立自动化智能维护的电子维护原则：从传感器级别到管理决策的过渡。在集成架构中，我们将深入研究一些研究挑战：-固定和移动的参与者之间交换维护数据的要求，例如铁路或航空航天应用中的轨道到列车数据交换。在移动的平台上实现监控自动化，并与其他参与者和固定系统进行交互。新的成本建模工具，用于复杂的分布式运行状况监控，尤其是对业务的价值。新颖之处在于实施有效的信息流和分析技术，以支持优化和基于不确定性的资源调度，捕获与数据滞后作斗争的业务"拉动"，以及将其转化为决策信息的工具不足。宗旨和目标：总体目标是在自动化、智能化的维护中，在数据丰富的环境中实现架构级别之间的集成，响应业务需求并展示价值。目标：-在技术丰富的数据源背景下，识别工厂和固定资产管理信息的工业需求，以便做出维护决策;即自上而下设计基于状态的维护。-架构级别之间的转换，从数据到信息再到决策，在适当的硬件（如无线平台和RFID）中嵌入自动功能。固定和移动的参与者之间的转移。-在大型数据集的状态监测问题中改进数据融合。以业务流程的形式挖掘和优化重新配置维护数据的演示方法。成本、价值和效益的估算工具，经过验证的应用程序。在一个由工业"拉动"指导的计划中，四个工作包将涵盖-集成，具有里程碑意义的"智囊团"事件报告;数据/信息和信息/决策过渡的定义，通过工业案例说明;设计战略文件;最终报告。数据融合和移动的平台，具有里程碑意义：多个非同步传感器数据融合策略;融合多个非同步传感器数据的案例研究;自上而下的监控系统设计策略;报告/消息传递架构-概念验证。基于智能可重构业务流程的规划和调度，具有里程碑意义：与合作伙伴合作，识别一组代表性的业务流程;多目标优化框架;验证合作伙伴的示例。成本分析，具有里程碑意义：确定最佳实践成本建模方法，成本效益分析和价值分析;开发成本和价值模型;评估业务综合维护成本和效益的框架;评估分布式异构高完整性资产的寿命成本和效益的框架，以及工具集的验证。

项目成果

Uncertainty of Net Present Value calculations and the impact on applying integrated maintenance approaches to the UK rail industry

净现值计算的不确定性以及对英国铁路行业应用综合维护方法的影响

• 作者: Kirkwood L

Data Fusion Strategy for Precise Vehicle Location for Intelligent Self-Aware Maintenance Systems

智能自我感知维护系统精确车辆定位的数据融合策略

• DOI: 10.1109/isms.2015.37
• 发表时间: 2015
• 作者: Bevilacqua M

An autonomous system for maintenance scheduling data-rich complex infrastructure: Fusing the railways' condition, planning and cost

• DOI: 10.1016/j.trc.2018.02.010
• 发表时间: 2018-04-01
• 期刊: TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
• 影响因子: 8.3
• 作者: Durazo-Cardenas, Isidro;Starr, Andrew;Emmanouilidis, Christos
• 通讯作者: Emmanouilidis, Christos

An Intelligent Framework and Prototype for Autonomous Maintenance Planning in the Rail Industry

铁路行业自主维护规划的智能框架和原型

• DOI: 10.5220/0005462800830089
• 发表时间: 2015
• 作者: Blacktop K

An Intelligent Maintenance System For The Rail: Integrating Condition, Planning And Cost

铁路智能维护系统：整合状态、规划和成本

• 发表时间: 2015
• 作者: Durazo-Cardenas I