Cranfield University
AUTONOM – Integrated through life support for high-value systems EPSRC Grant No. EP/J011630 Autonomous and Intelligent Systems Programme Duration: 2013-2017
The AUTONOM project aims 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 industrial pull Transition between architectural levels: from data to information to decision Improved data fusion in condition monitoring problems in large data sets
Integration
Development of a methodology for mining and optimally reconfiguring maintenance data An estimation tool for cost, value and benefits; with validated application
Data fusion & mobile platforms
Developing a top- Capturing how down architecture stationary sensor for nodes and mobile data/information/ sensors can work decision structures together
Planning & scheduling
Cost analysis
Developing a multi-objective optimisation framework for planning and scheduling
Identify drivers, model and estimate the costs, value and availability
Provision of a reporting/message passing architecture and strategy for top-down monitoring system design
Location
Partner Data Views Maintenance Planning and Auditing
-Specific Needs -Current Collection -What is Required -What is Desired
Asset Utilisation
Autonomous Vehicle Operation
www.cranfield.ac.uk/sas/autonom Contact: Prof. Andrew Starr [email protected] +44 (0)1234758374
A methodology for mining and optimally reconfiguring maintenance data in the form of a business process
Tool & frameworks for estimating costs & benefits of integrated maintenance, estimating the through-life costs and benefits of distributed assets
The AUTONOM project aims 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 industrial pull Transition between architectural levels: from data to information to decision Improved data fusion in condition monitoring problems in large data sets
Integration
Development of a methodology for mining and optimally reconfiguring maintenance data An estimation tool for cost, value and benefits; with validated application
Data fusion & mobile platforms
Developing a top- Capturing how down architecture stationary sensor for nodes and mobile data/information/ sensors can work decision structures together
Planning & scheduling
Cost analysis
Developing a multi-objective optimisation framework for planning and scheduling
Identify drivers, model and estimate the costs, value and availability
Provision of a reporting/message passing architecture and strategy for top-down monitoring system design
Location
Partner Data Views Maintenance Planning and Auditing
-Specific Needs -Current Collection -What is Required -What is Desired
Asset Utilisation
Autonomous Vehicle Operation
www.cranfield.ac.uk/sas/autonom Contact: Prof. Andrew Starr [email protected] +44 (0)1234758374
A methodology for mining and optimally reconfiguring maintenance data in the form of a business process
Tool & frameworks for estimating costs & benefits of integrated maintenance, estimating the through-life costs and benefits of distributed assets
