BRUCE ERNEST ALDRIDGE
Pilots at Calle Marbella, Oceanside, CA

6691120, Feb 10, 2004

Jun 30, 2000

09/608085

Douglas J. Durrant - Mission Viejo CA
Bruce E. Aldridge - Oceanside CA

NCR Corporation - Dayton OH

G06F 1730

707100, 7071041, 707 2, 707 4

A method and system for preparing a data record with multidimensional attributes for processing by a data-mining tool includes the steps of identifying a normalized data record, which includes an existing attribute comprising a plurality of dimensions, and generating a plurality of new attributes corresponding to the plurality of dimensions of the existing attribute. The method further includes creating an REI data record comprising the plurality of new attributes. The method further includes associating a plurality of value instances corresponding to the dimensions of the existing attribute with the plurality of new attributes.

8126767, Feb 28, 2012

Aug 9, 2004

10/742966

Bruce E. Aldridge - Oceanside CA, US
Rangarajan S. Thirumpoondi - Irvine CA, US

Teradata US, Inc. - Dayton OH

G06Q 10/00

705 736

A method of systematically applying parameter evaluation techniques to large numbers of complex segmented models used for managing and analyzing a segmented manufacturing or supply chain process. These models include a plurality of segment models, each segment model representing a process segment within the segmented manufacturing or supply chain process and comprising a mathematical expression including at least one parameter. The method compares predicted values generated by a segment model with actual observed values to determining a score representative of the performance of the segment model. New parameters for the mathematical equation associated with the segment model are determined through statistical techniques when the model score indicates an unacceptable performance of the segment model. The segment models may be evaluated and updated in parallel and without manual intervention.

7376601, May 20, 2008

Aug 18, 2004

10/920667

Bruce E. Aldridge - Oceanside CA, US

Teradata US, Inc. - Miamisburg OH

G06Q 10/00

705 28, 705 26

A method and system for determining shelf life and sell-through time for retail products. The solution employs a data warehouse, a self monitoring product and product traceability. The data warehouse is utilized to track delivery information throughout the supply chain, e. g. , time, quantity, product information, traceability; return information of unsold inventory returned from a retailer or customer as saleable; return information of inventory returned as unsaleable, damaged or defective; and data relating to evaluation of returned inventory. A self monitoring product is one that is capable of recording events such as number of times the product has been used, time since initial use, cumulative time and other items of interest such as stress variables, dates, min/max values, updates, etc. The solution involves evaluation of all returned product and comparing the information on the self monitoring product with known information from the supply line and return results contained in the database. The returns effectively act as a sample of all products and provide information about the product shelf-life, use profiles, installation issues, abuse, defects, etc.

7292905, Nov 6, 2007

Mar 31, 2000

09/541137

Douglas J. Durrant - Mission Viejo CA, US
Bruce E. Aldridge - Oceanside CA, US
Ross E. Gough - Foothill Ranch CA, US

NCR Corp. - Dayton OH

G06F 19/00

700108, 700115, 702182

A method and system for identifying manufacturing anomalies in a manufacturing system comprising a plurality of products which are manufactured with a plurality of manufacturing parameters is disclosed. The system comprises a data mining program applied to the data warehouse for analyzing the stored manufacturing parameters to define a normal manufacturing parameter subset. The data mining program is further for detecting that at least one of the plurality of manufacturing parameters is excluded from the normal subset. The system further comprises a reporting means for reporting the at least one detected manufacturing parameter. The data mining program may further detect that a plurality of the manufacturing parameters are excluded from the first subset. The data mining program then analyzes the detected plurality of manufacturing parameters to define a second normal subset of the detected plurality of manufacturing parameters. The reporting means may then report the second normal subset of manufacturing parameters.

6922684, Jul 26, 2005

Aug 31, 2000

09/652974

Bruce E. Aldridge - Oceanside CA, US
Gerald L. Hill - Huntington Beach CA, US
Craig I. Petz - San Diego CA, US

NCR Corporation - Dayton OH

G06N005/04

706 60, 706 45, 706 46

The present invention concerns an analytical-decision support system for improving management of quality and cost of a product throughout the entire product lifecycle of the product. The system comprises an atomic level data store for collecting data on component information, configuration information, and field information. A product-lifecycle-management analytics subsystem is included comprising: a query engine for compiling subsets of data from the atomic level data store; a first analysis tool for performing cost or quality analysis on the subsets to determine first analysis results; and a second analysis tool for analyzing detailed data in the atomic level data store to produce second analysis results. A management and operation subsystem is included for presenting the first analysis results after the first analysis tool performs the cost or quality analysis, and for presenting the second analysis results after the second analysis tool analyzes the detailed data. The management and operation subsystem further comprises: a user interface for receiving configuration data from a user for configuring the second analysis tool; and a warning notification subsystem for delivering warning notifications based on the first analysis results.

6847924, Jan 25, 2005

Jun 19, 2000

09/596635

Bruce E. Aldridge - Oceanside CA, US
Douglas J. Durrant - Mission Viejo CA, US

NCR Corporation - Dayton OH

G06F 760, G06F 1710, G06F10100

703 2, 703 1, 703 6, 702179, 702180, 702181

A system and method for creating an aggregated data model from a plurality data distribution models having bins approximating data elements in a plurality of data distributions is disclosed. Each bin of each data distribution model has a polynomial formula for approximating data elements in a respective data distribution. A method for creating the aggregated data model comprises: determining a start point of the aggregated data model having the minimum value and an end point having a maximum value of all of the bins of all of the data distribution models; setting a start point of a first bin of the aggregated data model; setting an end point of a last bin of the aggregated data model; determining a total number of points for the aggregated data model; approximating the data elements described by each data distribution model, each approximated data element comprising one point in the aggregated data model; sorting the points from minimum to maximum; distributing the points into one or more bins in the aggregated data model; and determining a polynomial formula for the points for each bin of the aggregated data model.

2008002, Jan 31, 2008

Jul 28, 2006

11/495388

Bruce E. Aldridge - Oceanside CA, US

G06F 17/10

703 2

A computer-implemented method for modeling a process sequence, includes constructing the process sequence, wherein the process sequence includes one or more paths comprising one or more steps connecting the process sequence start with the process sequence finish, building at least one histogram model for each step, combining the histogram models for each step into an aggregated histogram model for each path, and combining the aggregated histogram models for each path into an aggregated histogram model for the process sequence.

2011009, Apr 21, 2011

Feb 10, 2010

12/703493

Bruce E. Aldridge - Oceanside CA, US

TERADATA US, INC. - Miamisburg OH

G06F 17/30, G06F 7/22

707752, 703 2, 707607, 707E17104, 707E17045

A computer-implemented method for estimation of order-based statistics on slowly changing distributions of data stored on a computer. An initial set of data is converted to an initial histogram based representation of the data set's distribution. New or removed data is converted into a new histogram separate from the initial histogram. The new histogram is combined with the initial histogram to build a combined histogram. Percentiles and order-based statistics are estimated from the combined histogram to provide analysis of a combination of the initial set of data combined with the new or removed data.