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

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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.