Abstract: Advanced statistical detection of emerging trends in a process is disclosed, based on a Repeated Weighted Geometric Cumulative Sum analysis, which may be combined with time window-based estimation of proportions and related thresholds. Threshold derivation and significance computation is based on parallel simulation runs with power-exponential tail approximations. A battery of tests using the statistical theory of sequential analysis and change-point theory in combination with targets is used to evaluate non-conforming conditions in a process. Trends in fall-out rates are detected based on non-time-to-failure data that corresponds to counts of failures in consecutive time periods, with possibility of delayed input.

Abstract: An asymmetric approach is used for evaluating process control data, whereby one approach is used for determining entry into the emerging life cycle phase (i.e., presence of a new defect) and a different approach is used for detecting entry into the other life cycle phases such as cresting and recovering. An evidence curve is created from observed instance data for a particular defect, and the slope of this evidence curve is analyzed programmatically by applying one or more tests, in combination with sequential time-reversed estimation, to determine return-to-normal conditions with a desired level of confidence.

Abstract: An asymmetric approach is used for evaluating process control data, whereby one approach is used for determining entry into the emerging life cycle phase (i.e., presence of a new defect) and a different approach is used for detecting entry into the other life cycle phases such as cresting and recovering. An evidence curve is created from observed instance data for a particular defect, and the slope of this evidence curve is analyzed programmatically by applying one or more tests, in combination with sequential time-reversed estimation, to determine return-to-normal conditions with a desired level of confidence.

Abstract: Advanced statistical detection of emerging trends in a process is disclosed, based on a Repeated Weighted Geometric Cumulative Sum analysis, which may be combined with time window-based estimation of proportions and related thresholds. Threshold derivation and significance computation is based on parallel simulation runs with power-exponential tail approximations. A battery of tests using the statistical theory of sequential analysis and change-point theory in combination with targets is used to evaluate non-conforming conditions in a process. Trends in fall-out rates are detected based on non-time-to-failure data that corresponds to counts of failures in consecutive time periods, with possibility of delayed input.

Abstract: Determining a suitable target for an entity (such as a product) in a process control environment, based on observed process control data.

Abstract: Determining a suitable target for an entity (such as a product) in a process control environment, based on observed process control data.