Abstract: Methods and systems for detecting a fault in a data set from an industrial process are disclosed. One method includes forming a first data matrix at a data processing framework from time-series training data, and performing a principal component pursuit on the first data matrix to form an uncorrupted, unscaled matrix and a sparse matrix in the memory, and scaling the uncorrupted, unscaled matrix to form an uncorrupted scaled matrix. The method also includes performing a dynamic principal component analysis (DPCA) on the uncorrupted scaled matrix to form a DPCA model, and determining a squared prediction error from the DPCA model. Based on the squared prediction error, faults are detected in a different data set from operation of the industrial process. At least one of (1) correcting the one or more faults in the different data set or (2) performing a repair operation on a sensor is performed.

Abstract: Methods and systems for detecting a fault in a data set from an industrial process are disclosed. One method includes forming a first data matrix at a data processing framework from time-series training data, and performing a principal component pursuit on the first data matrix to form an uncorrupted, unscaled matrix and a sparse matrix in the memory, and scaling the uncorrupted, unscaled matrix to form an uncorrupted scaled matrix. The method also includes performing a dynamic principal component analysis (DPCA) on the uncorrupted scaled matrix to form a DPCA model, and determining a squared prediction error from the DPCA model. Based on the squared prediction error, faults are detected in a different data set from operation of the industrial process. At least one of (1) correcting the one or more faults in the different data set or (2) performing a repair operation on a sensor is performed.

Abstract: A method and an apparatus are provided for applying a self-adaptive filter to a drifting process. The method includes processing a workpiece, measuring an output characteristic of the processed workpiece and modifying a previous estimated process state based at least on the measured output characteristic. The method further includes estimating a next process state based at least on the modified previous estimated process state.

Abstract: Methods of optimizing a preheat recipe for rapid thermal processing workpieces are provided. In one aspect, a method of manufacturing is provided that includes preheating a rapid thermal processing chamber according to a preheating recipe and processing a first plurality of workpieces in the rapid thermal processing chamber. Parameter measurements are performed on a first workpiece and a second workpiece of the first plurality of workpieces. The parameter measurements are indicative of processing differences between the first and second workpieces. An output signal is formed corresponding to the parameter measurements and a control signal based on the output signal is used to adjust the preheating recipe for preheating the rapid thermal processing chamber for processing a second plurality of workpieces in the rapid thermal processing chamber to reduce processing differences between first and second workpieces of the second plurality of workpieces.