Resumen de Ontology-based uncertainty management approach in designing of robust decision workflows
Ru Wang, Anand Balu Nellippallil, Guoxin Wang, Yan Yan, Janet K. Allen, Farrokh Mistree
The formal representation and capturing of uncertainty knowledge are always essential but difficult. Typically, the uncertainties due to incompleteness and inaccuracies of model information in engineering design necessitate the designing of robust decision workflows to improve the quality of process/product in variations. This requests extending a designer's abilities in managing various uncertainties in system design and making decisions that are robust, flexible, and comprehensive. To enable the management of various uncertainties, in this paper, we propose an ontology for robust design and a template-based ontological method that is employed to design decision workflows. We achieve the aforementioned goals through the identification of: (1) procedural knowledge – defining a procedure of designing robust decision workflows, including the sequence of activities, to determine the right combination of design information for a specific type of uncertainty, and (2) declarative knowledge – developing a frame-based ontology for the formal representation of tacit knowledge to capture and document the re-usable information of a robust design by utilising the process templates. We demonstrate the efficacy by carrying out the robust design of the hot rod rolling process based on the analysis and synthesis of the processing-microstructure (cooling module) and the microstructure-mechanical (rod module) simulation models.
