Abstract: A computer-implemented method includes assigning an auditor weight to each user of a plurality of users. A plurality of audit data is received from the plurality of users, where each audit data is associated with a respective user and includes a set of user ratings for an audit. Final ratings are generated for the audit, with a respective final rating for each item in the audit. Generating the final rating of a first item in the audit includes identifying, in the audit data, user ratings for the first item. The user ratings for the first item include a respective user rating of the first item from each user. Generating the final rating of a first item further includes calculating the final rating of the first item based on a weighted combination of the plurality of user ratings for the first item, according to the respective auditor weight of each user.

Abstract: In an approach for storage optimization for products manufacturing, a processor pulls parts data for a set of part numbers. A processor calculates an average shelf time for each part number of the set of part numbers. A processor calculates a priority index for each part number of the set of part numbers based on the average shelf time for each part number of the set of part numbers. A processor determines a category for each part number of the set of part numbers based on the priority index for each part number of the set of part numbers and a quantity of parts cumulative percentage for each part number of the set of part numbers.

Abstract: In an approach for storage optimization for products manufacturing, a processor pulls parts data for a set of part numbers. A processor calculates an average shelf time for each part number of the set of part numbers. A processor calculates a priority index for each part number of the set of part numbers based on the average shelf time for each part number of the set of part numbers. A processor determines a category for each part number of the set of part numbers based on the priority index for each part number of the set of part numbers and a quantity of parts cumulative percentage for each part number of the set of part numbers.

Abstract: A computer-implemented method includes receiving a plurality of values of a data stream, where the plurality of values are generated by a monitored device and received in real time. One or more statistical moments of the data stream are updated, by a computer processing device, based on each value of the plurality of values. Each value of the plurality of values is discarded, after updating the one or more statistical moments of the data stream based on that value. A threshold is set for the data stream based on the one or more statistical moments. It is detected that the threshold has been passed by the data stream. A remedial action is performed on the monitored device, responsive to the threshold being passed, where the remedial action is associated with the threshold.

Abstract: A computer-implemented method includes assigning an auditor weight to each user of a plurality of users. A plurality of audit data is received from the plurality of users, where each audit data is associated with a respective user and includes a set of user ratings for an audit. Final ratings are generated for the audit, with a respective final rating for each item in the audit. Generating the final rating of a first item in the audit includes identifying, in the audit data, user ratings for the first item. The user ratings for the first item include a respective user rating of the first item from each user. Generating the final rating of a first item further includes calculating the final rating of the first item based on a weighted combination of the plurality of user ratings for the first item, according to the respective auditor weight of each user.

Abstract: A computer-implemented method includes receiving a plurality of values of a data stream, where the plurality of values are generated by a monitored device and received in real time. One or more statistical moments of the data stream are updated, by a computer processing device, based on each value of the plurality of values. Each value of the plurality of values is discarded, after updating the one or more statistical moments of the data stream based on that value. A threshold is set for the data stream based on the one or more statistical moments. It is detected that the threshold has been passed by the data stream. A remedial action is performed on the monitored device, responsive to the threshold being passed, where the remedial action is associated with the threshold.

Abstract: A computer-implemented method includes receiving a plurality of values of a data stream, where the plurality of values are generated by a monitored device and received in real time. One or more statistical moments of the data stream are updated, by a computer processing device, based on each value of the plurality of values. Each value of the plurality of values is discarded, after updating the one or more statistical moments of the data stream based on that value. A threshold is set for the data stream based on the one or more statistical moments. It is detected that the threshold has been passed by the data stream. A remedial action is performed on the monitored device, responsive to the threshold being passed, where the remedial action is associated with the threshold.

Abstract: A computer-implemented method includes receiving a plurality of values of a data stream, where the plurality of values are generated by a monitored device and received in real time. One or more statistical moments of the data stream are updated, by a computer processing device, based on each value of the plurality of values. Each value of the plurality of values is discarded, after updating the one or more statistical moments of the data stream based on that value. A threshold is set for the data stream based on the one or more statistical moments. It is detected that the threshold has been passed by the data stream. A remedial action is performed on the monitored device, responsive to the threshold being passed, where the remedial action is associated with the threshold.

Abstract: A method for problem remediation in supply chain management is provided in the illustrative embodiments. A determination is made whether a data in a data stream of a supply chain process is indicative of a problem in the supply chain. Responsive to determining that the data is indicative of the problem, a confidence level is assigned to a diagnosis of the problem. Using a historical data repository, a symptom of the problem is identified. The symptom identifies a point in the data stream where the problem is manifested. Using the historical database, a remedy for the problem is identified. The remedy is recorded in the historical data repository with the problem and the symptom at a previous time. The previous time is before receiving the data stream. The remedy is applied to the supply chain.

Abstract: A system, and computer program product for problem remediation in supply chain management are provided in the illustrative embodiments. A determination is made whether a data in a data stream of a supply chain process is indicative of a problem in the supply chain. Responsive to determining that the data is indicative of the problem, a confidence level is assigned to a diagnosis of the problem. Using a historical data repository, a symptom of the problem is identified. The symptom identifies a point in the data stream where the problem is manifested. Using the historical database, a remedy for the problem is identified. The remedy is recorded in the historical data repository with the problem and the symptom at a previous time. The previous time is before receiving the data stream. The remedy is applied to the supply chain.

Abstract: Data associated with supply chain events for a manufactured assembly is automatically stored. In preferred embodiments the supply chain events for the manufactured assembly are stored on an RFID tag attached to the assembly as it travels through the supply chain to insure the data concerning the assembly is readily available and not separated from the assembly. In other embodiments, the supply chain events or characteristic data is stored on the RFID tag in a hierarchical structure beginning with the original state of the assembly and with additional entries for each step in the assembly process. In other embodiments, as the product undergoes rework, conversion to a different assembly, or personalizations, the new state of the assembly is stored in the RFID tag. In other preferred embodiments, other information is also stored on the RFID tag such as country of origin, failure data, cycle times and a quality status indicator.

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: 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.

Abstract: A data processing system for analyzing rejection rejections in a manufacturing process having more than one level of manufacture stores test results from an nth-level test for review by an OEM and, subject to consent of the nth level vendor, for review by a vendor on a lower level. The data for rejection analysis is linked to data in a manufacturing floor control system.

Abstract: A method and system makes date-time conversions and complex date-time calculations between dates of different calendaring systems. The conversion method herein allows embedded, real-time conversion in computer applications and systems between multiple calendaring systems. A date of a first date-time format is converted to any date of a second date-time format after a transformation to a temporal reference or epoch date. The conversion method can be embedded into any code space to enable full date-time conversion abilities. The real-time conversion of the conversion method requires no conversion tables and no post-processing manipulation thus eliminating the need for individual programmers to re-create the same date cross reference tables, or post processing algorithms. The conversion method supports conversion between any two date-time formats including the various existing Gregorian conventions.

Abstract: An exemplary embodiment of the invention relates to a method, system, and storage medium for providing a dynamic multi-dimensional commodity modeling process. The system includes a data collection component operable for collecting raw data, a dynamic multi-dimensional commodity model component, and a commodity tree generated by the dynamic multi-dimensional commodity model component. The system also includes a closed loop/corrective action component operable for resolving nonconformance issues resulting from analysis of the raw data and commodity tree, and an analytic engine in communication with the data collection component, the multi-dimensional commodity model component, and the closed loop/corrective action component.