Organization of big metrology data within the Cyber-Physical Manufacturing Metrology Model (CPM3)

In this paper, we propose a novel data curation concept that enables data mining and analytics within the recently described Cyber-Physical Manufacturing Metrology Model (CPM3). The newly proposed methodology is based on organizing the metrology data into tree-based database structures using distance-based unsupervised clustering of the raw metrology data. Compared to traditionally utilized temporally organized lists, the new tree-based database organization of metrology data enables logarithmic acceleration of searches within the data and thus provides dramatic advantages for data mining. The newly proposed data curation methodology was evaluated in case studies involving hyper-spectral metrology of nanopatterned surfaces, coordinate measurement machine (CMM) inspection of aircraft engine turbines and imaging-based metrology of nano-volume droplets in the jet and fill stage of imprint lithography processes. Significant improvements in search speeds with minimal or no losses in search precision and recall were observed in all case-studies, with benefits of tree-based data organization growing with the size of the data.