Abstract: A method of multivariate spectral analysis, termed augmented classical least squares (ACLS), provides an improved CLS calibration model when unmodeled sources of spectral variation are contained in a calibration sample set. The ACLS methods use information derived from component or spectral residuals during the CLS calibration to provide an improved calibration-augmented CLS model. The ACLS methods are based on CLS so that they retain the qualitative benefits of CLS, yet they have the flexibility of PLS and other hybrid techniques in that they can define a prediction model even with unmodeled sources of spectral variation that are not explicitly included in the calibration model. The unmodeled sources of spectral variation may be unknown constituents, constituents with unknown concentrations, nonlinear responses, non-uniform and correlated errors, or other sources of spectral variation that are present in the calibration sample spectra.

Abstract: Apparatus and method for controlling metals processing (e.g., ESR) by melting a metal ingot and counting molten metal droplets during melting. An approximate amount of metal in each droplet is determined, and a melt rate is computed therefrom. Impedance of the melting circuit is monitored, such as by calculating by root mean square a voltage and current of the circuit and dividing the calculated current into the calculated voltage. Analysis of the impedance signal is performed to look for a trace characteristic of formation of a molten metal droplet, such as by examining skew rate, curvature, or a higher moment.