ENDPOINT DETECTION IN MANUFACTURING PROCESS BY NEAR INFRARED SPECTROSCOPY AND MACHINE LEARNING TECHNIQUES

A device may receive training spectral data associated with a manufacturing process that transitions from an unsteady state to a steady state. The device may generate, based on the training spectral data, a plurality of iterations of a support vector machine (SVM) classification model. The device may determine, based on the plurality of iterations of the SVM classification model, a plurality of predicted transition times associated with the manufacturing process. A predicted transition time, of the plurality of predicted transition times, may identify a time, during the manufacturing process, that a corresponding iteration of the SVM classification model predicts that the manufacturing process transitioned from the unsteady state to the steady state. The device may generate, based on the plurality of predicted transition times, a final SVM classification model associated with determining whether the manufacturing process has reached the steady state.