18. AI for textile machinery configuration 26/05/10 [email_address] Raw materials parameters Machinery settings parameters End product parameters RP1 RP2 RP3? RP4 RP 5 ? RP1 RP2 RP3 RP4 RP5 MP1? MP2 MP3 MP4 MP5 MP1 MP2 MP3 MP4 MP5 EP1 EP2? EP3 EP4 EP5? EP1 EP2 EP3 EP4 EP5 CBR System Diameter Fiber Fiber density Cylinder speed twist Porosity Predicted value Required value To make easier the production of new advanced textile products Prediction of the required unknown parameters To reduce the economical cost and time required for the textile machinery set-up Doing less tests in the textile machines Case-Based Reasoning: Using previous process experiential knowledge
26. new WS Existing platforms Existing services New services Service interactions Service level: - semantic service description (SD) - standards specification role actual deployment Methodology Framework Coordination level: - coordination patterns - task allocation - actor expectation Organizational level: - norms and regulations - organizational structure - communication ontology - evaluation indicators WS WS WS WS WS SD SD SD SD SD SD actor actor actor actor dynamic assignment Functional instantiation role role role WHY? (motivations) WHAT? (possible actions, plans) HOW? (available services)
27. AI for flexible, adaptive on-line systems A set of services is selected to fulfill a user request. The service selected for the “find museum info” task fails … No alternate service is found for the task re-plan A new set of services is invoked and the results merged to fulfill the user request.
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Notas do Editor
Comentarios: Isabel Corral Navaz & Jordi Segura Pla