CBR Maintenance Analysis Engine Model Simulation Workflow Advisor Mobile Grid Support
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DESCRIPTIONThe University of Sheffield DAME Team Prof Peter Fleming Prof Haydn Thompson Dr Visakan Kadirkamanathan Jeff Allan Max Ong Xiaoxu Ren Luka Eciolaza Alex Shenfield Muhammad Alkarouri. CBR Maintenance Analysis Engine Model Simulation Workflow Advisor Mobile Grid Support. Retrieve. - PowerPoint PPT Presentation
CBR Maintenance Analysis
Engine Model Simulation
Mobile Grid SupportThe University of SheffieldDAME Team
Prof Peter Fleming
Prof Haydn Thompson
Dr Visakan Kadirkamanathan
Max OngUniversity of Sheffield, UK.Case-Based Reasoning for Decision Supportin DAME Case-Based Reasoning (CBR) is a problem-solving paradigm that resolves new problems by adapting the solutions used to solve problems of a similar nature in the past. This approach allows consolidation of rule knowledge and provides a reasoning engine that is capable of probabilistic-based matching. With CBR technology, development can take place in an incremental fashion facilitating rapid prototyping of an initial system. The development of robust strategies for integration of multiple health information sources can be achieved with reasoning algorithms of progressively increasing complexity. In the distributed DAME diagnostic environment, CBR is accessed by maintenance engineers across the Grid for collaborative problem solving.
CBR Maintenance Analysis Grid Service Integrates fault information and knowledge gained from fault diagnosis process Emulates the diagnostic skill of an experienced maintenance engineer Advises maintenance personnel on appropriate maintenance action Deployed as a service on the Grid Accessible by user via a Web browser across the Internet Secure access with user and host authentication, X509 digital certificates and SSL encryption.
CBR Maintenance Analysis Grid Service A Grid-enabled CBR engine developed at Sheffield University has been deployed as a Grid Service. In DAME, aircraft maintenance engineers are able to access this secure service across the Internet via a Web browser. Maintenance engineers are able to perform knowledge-based searches and reasoning across stores of accumulated diagnostic knowledge and maintenance data with the support of Grid computing resources to assist the fault analysis and decision-making process.
Xiaoxu RenUniversity of Sheffield, UK.Engine Simulation Grid Service for DAMEBy using the Grid technologies, different modelling, simulation, and fault diagnostic approaches from different providers or institutes can be shared, coordinated and integrated to deliver desired QoS for fault diagnostics, prognostics and engine maintenance.
Engine Simulation Grid Service As one effort carried out in Sheffield on the DAME project, a Rolls-Royce aero gas turbine engine performance model was wrapped and provided as a Grid service.Based on the Globus Toolkit 3, the Open Grid Service Implementation(OGSI) for distributed systems integration, this engine simulation Grid service can be invoked simultaneously in different Virtual Organisations for different applications.Features:The Factory Service can generate a bunch of engine simulation instances for different client requirementsMessage Level Security are implemented to protect the secure sensitive engine model and user dataUse Web browser to access the engine performance data and simulation resultsTwo way SSL authentication via server and client certificates
Engine Simulation Grid ServiceProvides GSI enabled secure engine performance simulation for different flight operational conditions and requirements, e.g. Idle, take-off, climb, cruise;Takes different variables, including Net Thrust, Turbine Temperature, Spool Speed and Fuel Flow, as control input;Can be used to assist the experienced maintenance engineers to find the problem via on-line simulation;Can be invoked by different fault diagnostic algorithms to facilitates the exploitation of further development and analysis of different model-based fault detection and Isolation (FDI) approaches.
Applications: A simulation-based fault detection can be performed Experienced maintenance engineers can use this service to find the problem via on-line simulation Can be used to confirm the fault assumption Can be invoked by different fault diagnostic algorithmsSimulator-based approach
Max OngUniversity of Sheffield, UK.AHM 2004 Session 2.3: Workflow Composition, Wednesday 1st September 2004, 4pm.Workflow Advisor in DAMEAbstract. There are an increasingly large number of web services available today. New services are constantly being introduced, each performing different tasks ranging from simple data transfer operations to highly complex engineering and mathematical processes. There is an emerging need for the ability to dynamically discover how available services, resources and data could be utilised not only to process a task, but to achieve the desired outcome in the most suitable manner. This paper investigates the emerging need for workflow advice to aid decision support on the Grid and proposes a workflow advice system that incorporates a reasoning system designed to perform such a task. The case for a Workflow Advisor system is explored within the context of advanced aero engine fault diagnostics in the UK e-Science Grid project, DAME.
Workflow AdvisorNew Web Services are constantly being introduced every day, each performing different tasks ranging from simple data transfer operations to highly complex engineering and mathematical processes.Open standards have enabled inter-operability between resources available across the virtual Grid computing environment.However, there is an emerging need for the ability to dynamically discover how these available services, resources and data could be best utilised and integrated not only to process a task, but to achieve the desired outcome in the most suitable manner.Key challenges:To provide the best advice on constructing complex workflows using the available Grid-enabled resources to complete a desired taskTo provide the underlying knowledge capture and knowledge-based techniques for search and reasoning across complex workflow information to support that advice.
Workflow Advisor in use within the DAME Grid portal. Workflows are being recommended for execution in a birdstrike diagnosis scenarioSelection and composition of individual services into a set of workflow processes is crucial to perform a task correctly.There may exist more than one way to perform a task. It would be ideal to be able to explore every possibility and compare all end results.However, given the time-constraints, human-resource factors and costs involved in a real-world application, it is highly advantageous to have an intelligent system that can: Provide the user with knowledge on how available services can be utilised to achieve a desired objective beforehand Reduce the time taken to complete a job Advise on how best to utilise an available resourceThis is particularly important when: A user is unfamiliar with available services and resources but needs to perform a task A particular service or resource is scarce or expensive A particular process is time-consuming or not readily available
Very few Grid projects to date have made use of intelligence to guide users through workflows in complex systems.In DAME sophisticated, but generic, CBR tools are used to yield a ranked analysis of relevant case histories followed by a rule-base which guides the aircraft maintenance engineer through a set of actions.Capturing domain knowledge and evaluation of workflow results is the key to creating suitable new workflows for new tasks.The service-oriented, collaborative Workflow Advisor developed in DAME allows new forms of advice and guidance to be offered to users.Workflow Advisor facilitates personalisation of workflow composition by individual users as well as allows collaboration between users in the problem-solving process.Events within units, sub-modules, and main modules of a complex system of interactions may lead to information that can be analysed by a multitude of tools, and where not only the collaboration of engine experts may be of value, but also the capturing of wide ranging knowledge and experience within the aircraft maintenance environment.
Muhammad AlkarouriUniversity of Sheffield, UK.Mobile Grid Decision Support Recently the concept of computing is becoming increasingly less confined to the traditional computing platforms of PCs and mainframes. While grid computing promises the accessibility of vast computing and data resources across geographically dispersed areas, there is no current established support for mobile user access. Access to the grid from mobile devices can be very effective in business environments. Users can have access to the computing power and data repositories on the Grid, while working on the field. Mobile access also enables and encourages distributed collaborative work environments.
Challenges faced in Mobile Grid Decision SupportA mobile device has various issues involved, such as: Hardware constraints: small processing power and memory. This means that any kind of middleware should be efficiently implemented and may exclude the use of some complicated algorithms, and programming environments like J2EE and .Net Small display space, which makes presentation of data to human users more difficult. Services must be written or adapted to use small display space. Standard Grid security implementations are currently unsuitable for small and mobile devices, as they use large processing power and/or memory. Non trivial quality of service required Mobility places additional constraints for quality of service control.
Implementation of Mobile Grid Decision SupportAn implementation of Grid access service, from a wireless device, has been developed at the University of Sheffield. Uses a HP iPaq moble wireless PDA device Operating system is Linux, a handheld version (Familiar Linux). Use of open source e