Hy D. Tran

A Lipschitz Regularity-Based Statistical Model With Applications in Coordinate Metrology

In dimensional inspection using coordinate measuring machines (CMMs), the following issues are critical to achieve accurate inspection while minimizing the cost and time: 1) How can we select the sampling positions of the measurements so that we can get as much information from a limited number of samples as possible and 2) given the limited number of measurements, how can we assess the form error so that one can reliably decide whether the product is acceptable? To address these problems, we propose a wavelet-based model that takes advantage of the fact that the Lipschitz regularity holds for the CMM data. Under the framework of the proposed model, we derive the optimal sampling positions and propose a systematic procedure to estimate the form error given the limited number of sampled points. The proposed method is validated using both synthetic and real CMM data sets for straightness measurements. The comparison with other existing methods demonstrates the effectiveness of our method.

Determination and Optimization of Spatial Samples for Distributed Measurements

There are no accepted standards for determining how many measurements to take during part inspection or where to take them, or for assessing confidence in the evaluation of acceptance based on these measurements. The goal of this work was to develop a standard method for determining the number of measurements, together with the spatial distribution of measurements and the associated risks for false acceptance and false rejection. Two paths have been taken to create a standard method for selecting sampling points. A wavelet-based model has been developed to select measurement points and to determine confidence in the measurement after the points are taken. An adaptive sampling strategy has been studied to determine implementation feasibility on commercial measurement equipment. Results using both real and simulated data are presented for each of the paths.

Design of a Silicon Micromachined Artifact for Hybrid Dimensional Measurement

We are developing calibration artifacts for mesoscale metrology (especially vision probing) by using silicon bulk micromachining. We evaluate these artifacts on both high accuracy coordinate measuring machines (CMMs) and on typical production vision-based measurement systems. This will improve the accuracy of vision-based measurement equipment used in production. Successful realization of these mesoscale artifacts will enhance both production metrology capabilities and reduce manufacturing costs.Copyright

Calculating Measurement Uncertainty of the “Conventional Value of the Result of Weighing in Air”

Abstract: The conventional value of the result of weighing in air is frequently used in commercial calibrations of balances. The guidance in OIML D-028 for reporting uncertainty of the conventional value is too terse. When calibrating mass standards at low measurement uncertainties, it is necessary to perform a buoyancy correction before reporting the result. When calculating the conventional result after calibrating true mass, the uncertainty due to calculating the conventional result is correlated with the buoyancy correction. We show through Monte Carlo simulations that the measurement uncertainty of the conventional result is less than the measurement uncertainty when reporting true mass.

Silicon Bulk Micromachined Hybrid Dimensional Artifact

A mesoscale dimensional artifact based on silicon bulk micromachining fabrication has been developed and manufactured with the intention of evaluating the artifact both on a high precision coordinate measuring machine (CMM) and video-probe based measuring systems. This hybrid artifact has features that can be located by both a touch probe and a video probe system with a k=2 uncertainty of 0.4 {micro}m, more than twice as good as a glass reference artifact. We also present evidence that this uncertainty could be lowered to as little as 50 nm (k=2). While video-probe based systems are commonly used to inspect mesoscale mechanical components, a video-probe systems certified accuracy is generally much worse than its repeatability. To solve this problem, an artifact has been developed which can be calibrated using a commercially available high-accuracy tactile system and then be used to calibrate typical production vision-based measurement systems. This allows for error mapping to a higher degree of accuracy than is possible with a glass reference artifact. Details of the designed features and manufacturing process of the hybrid dimensional artifact are given and a comparison of the designed features to the measured features of the manufactured artifact is presented and discussed. Measurement results from vision and touch probe systems are compared and evaluated to determine the capability of the manufactured artifact to serve as a calibration tool for video-probe systems. An uncertainty analysis for calibration of the artifact using a CMM is presented.