Measurement, visualization and analysis of extremely large data sets with a nanopositioning and nanomeasuring machine

O. Birli; K.-H. Franke; G. Linß; T. Machleidt; E. Manske; F. Schale; H.-C. Schwannecke; E. Sparrer; M. Weiß

doi:10.1117/12.2020538

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13 May 2013 Measurement, visualization and analysis of extremely large data sets with a nanopositioning and nanomeasuring machine

O. Birli, K.-H. Franke, G. Linß, T. Machleidt, E. Manske, F. Schale, H.-C. Schwannecke, E. Sparrer, M. Weiß

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Proceedings Volume 8788, Optical Measurement Systems for Industrial Inspection VIII; 87880X (2013) https://doi.org/10.1117/12.2020538
Event: SPIE Optical Metrology 2013, 2013, Munich, Germany

Abstract

Nanopositioning and nanomeasuring machines (NPM machines) developed at the Ilmenau University of Technology allow the measurement of micro- and nanostructures with nanometer precision in a measurement volume of 25 mm × 25 mm × 5 mm (NMM-1) or 200 mm × 200 mm × 25 mm (NPMM-200). Various visual, tactile or atomic force sensors can all be used to measure specimens. Atomic force sensors have emerged as a powerful tool in nanotechnology. Large-scale AFM measurements are very time-consuming and in fact in a practical sense they are impossible over millimeter ranges due to low scanning speeds. A cascaded multi-sensor system can be used to implement a multi-scale measurement and testing strategy for nanopositioning and nanomeasuring machines. This approach involves capturing an overview image at the limit of optical resolution and automatically scanning the measured data for interesting test areas that are suitable for a higher-resolution measurement. These “fields of interest” can subsequently be measured in the same NPM machine using individual AFM sensor scans. The results involve extremely large data sets that cannot be handled by off-the-shelf software. Quickly navigating within terabyte-sized data files requires preprocessing to be done on the measured data to calculate intermediate images based on the principle of a visualization pyramid. This pyramid includes the measured data of the entire volume, prepared in the form of discrete measurement volumes (spatial tiles or cubes) with certain edge lengths at specific zoom levels. The functionality of the closed process chain is demonstrated using a blob analysis for automatically selecting regions of interest on the specimen. As expected, processing large amounts of data places particularly high demands on both computing power and the software architecture.

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O. Birli, K.-H. Franke, G. Linß, T. Machleidt, E. Manske, F. Schale, H.-C. Schwannecke, E. Sparrer, and M. Weiß "Measurement, visualization and analysis of extremely large data sets with a nanopositioning and nanomeasuring machine", Proc. SPIE 8788, Optical Measurement Systems for Industrial Inspection VIII, 87880X (13 May 2013); https://doi.org/10.1117/12.2020538

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