Abstract: A system, method, and computer-readable medium are disclosed performing an optimization operation. The optimization operation optimizes continuous processes by identifying process states associated with specific ranges for a limited subset of control parameter inputs. In certain embodiments, the optimization operation states comprise clear, stable, and robust process states. Such an optimization operation provides a simpler and cost effective means to optimize continuous processes. Additionally, such an optimization operation is applicable more rapidly to a wider range of real-world operational issues as they occur regularly in continuous process scenarios.

Abstract: A system, method, and computer-readable medium are disclosed for analysis and characterization of manufacturing information such as process trees or genealogies using graph theory. More specifically, using graph theory to analyze manufacturing information of a manufacturing operation allows for deep analysis of relationships between batches or units in a process tree and their closeness or distance, to identify clusters associated with specific quality characteristics or problems, to identify common antecedents of specifically labeled batches (e.g., problem batches), and/or to detect overall desirable or undesirable characteristics of the process tree (e.g., centrality, etc.).

Abstract: A system, method, and computer-readable medium are disclosed for analysis and characterization of manufacturing information such as process trees or genealogies using graph theory. More specifically, using graph theory to analyze manufacturing information of a manufacturing operation allows for deep analysis of relationships between batches or units in a process tree and their closeness or distance, to identify clusters associated with specific quality characteristics or problems, to identify common antecedents of specifically labeled batches (e.g., problem batches), and/or to detect overall desirable or undesirable characteristics of the process tree (e.g., centrality, etc.).

Abstract: A system, method, and computer-readable medium for extracting the samples from big data to extract most information about the relationships of interest between dimensions and variables in the data repository. More specifically, extracting information from large data repositories follows an adaptive process that uses systematic sampling procedures derived from optimal experimental designs to target from a large data set specific observations with information value of interest for the analytic task under consideration. The application of adaptive optimal design to guide exploration of large data repositories provides advantages over known big data technologies.

Abstract: A system, method, and computer-readable medium are disclosed for analysis and characterization of manufacturing information such as process trees or genealogies using graph theory. More specifically, using graph theory to analyze manufacturing information of a manufacturing operation allows for deep analysis of relationships between batches or units in a process tree and their closeness or distance, to identify clusters associated with specific quality characteristics or problems, to identify common antecedents of specifically labeled batches (e.g., problem batches), and/or to detect overall desirable or undesirable characteristics of the process tree (e.g., centrality, etc.).

Abstract: A system, method, and computer-readable medium are disclosed for analysis and characterization of manufacturing information such as process trees or genealogies using graph theory. More specifically, using graph theory to analyze manufacturing information of a manufacturing operation allows for deep analysis of relationships between batches or units in a process tree and their closeness or distance, to identify clusters associated with specific quality characteristics or problems, to identify common antecedents of specifically labeled batches (e.g., problem batches), and/or to detect overall desirable or undesirable characteristics of the process tree (e.g., centrality, etc.).

Abstract: A system, method, and computer-readable medium for extracting the samples from big data to extract most information about the relationships of interest between dimensions and variables in the data repository. More specifically, extracting information from large data repositories follows an adaptive process that uses systematic sampling procedures derived from optimal experimental designs to target from a large data set specific observations with information value of interest for the analytic task under consideration. The application of adaptive optimal design to guide exploration of large data repositories provides advantages over known big data technologies.

Abstract: A system, method, and computer-readable medium are disclosed performing an optimization operation. The optimization operation optimizes continuous processes by identifying process states associated with specific ranges for a limited subset of control parameter inputs. In certain embodiments, the optimization operation states comprise clear, stable, and robust process states. Such an optimization operation provides a simpler and cost effective means to optimize continuous processes. Additionally, such an optimization operation is applicable more rapidly to a wider range of real-world operational issues as they occur regularly in continuous process scenarios.

Abstract: A method is provided for deriving optimized operating parameter settings for industrial furnaces of different designs as commonly used in power generation that will achieve robust and desirable operations (for example, low NOx and low CO emissions while maintaining specific furnace exit gas temperatures). The method includes the application of recursive partitioning algorithms to historical process data to identify critical combinations of ranges of operational parameter (combinations of settings) that will result in robust (low-variability) desirable (optimized) boiler performance, based on empirical evidence in the historical data.

Abstract: A method of analyzing Stoneley waveforms obtained in a well logging operation, includes analyzing the waveforms by means of multiparameter inversion using one or more externally provided parameters to obtain borehole fluid slowness and borehole fluid attenuation. and analyzing the Stoneiey waveforms by multiparameter inversion using the borehole fluid slowness and borehole fluid attenuation and the externally provided parameters so as to determine a parameter, such as mobility, related to permeability of the formation being logged. Complex conjugate back propagation [using a maximum likelihood/least mean squares error estimator or] by applying Prony's method and fitting model-derived dispersion curves can be used to obtain mobility.

Abstract: A method of analyzing Stoneley waveforms obtained in a well logging operation, includes analyzing the waveforms by means of multiparameter inversion using one or more externally provided parameters to obtain borehole fluid slowness and borehole fluid attenuation, and analyzing the Stoneley waveforms by multiparameter inversion using the borehole fluid slowness and borehole fluid attenuation and the externally provided parameters so as to determine a parameter, such as mobility, related to permeability of the formation being logged. Complex conjugate back propagation using a maximum likelihood/least mean squares error estimator or by applying Prony's method and fitting model-derived dispersion curves can be used to obtain mobility.