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Mining Process Heuristics from Designer Action Data via Hidden Markov Models
[post]
2018
unpublished
Configuration design problems, characterized by the assembly of components into a final desired solution, are common in engineering design. Various theoretical approaches have been offered for solving configuration type problems, but few studies have examined the approach that humans naturally use to solve such problems. This work applies data-mining techniques to quantitatively study the processes that designers use to solve configuration design problems. The guiding goal is to extract
doi:10.31224/osf.io/c7pg6
fatcat:4o2szxo53rfmdpat6gbgd2o654