Uncertainty budget of a large-range nanopositioning platform based on Monte Carlo simulation

The objective of precision systems design is to obtain machines with very high and totally predictable work-zone accuracies. In already functional systems, where the errors can be measured, this achieved by error correction compensation. aim work propose an uncertainty budget methodology final measuring precise after case study a nanopositioning platform, referred as NanoPla, confocal sensor integrated instrument. NanoPla performs positioning in large range 50 mm × mm, its target surface topography characterization, at submicrometre scale. After performing Monte Carlo method used along whole working range, considering all casuistry. By studying results, authors are able solutions minimize uncertainty.