Christopher D Keener

age ~62

from San Jose, CA

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Christopher Keener Phones & Addresses

Method Of Testing For Response Abnormalities In A Magnetic Sensor
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US Patent:

6661223, Dec 9, 2003
Filed:

Jan 7, 2002
Appl. No.:

10/041282
Inventors:

Peter Cheng-I Fang - San Jose CA
Christopher Dana Keener - San Jose CA
Kenneth Donald Mackay - San Jose CA
Assignee:

International Business Machines Corporation - Armonk NY
International Classification:

G01R 3500
US Classification:

324210, 324202, 324228
Abstract:

A method is disclosed for determining the presence of response abnormalities in magnetic sensors. The method includes placing the sensor in an applied magnetic field and collecting sensor resistance information as the magnitude and direction of the applied field is altered. The resistance values are then examined to determine the presence of response abnormalities.

Method And Apparatus For Performing Spin Valve Combined Pinned Layer Reset And Hard Bias Initialization At The Hga Level
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US Patent:

6728055, Apr 27, 2004
Filed:

Mar 21, 2000
Appl. No.:

09/531618
Inventors:

Hardayal Singh Gill - Portola Valley CA
Christopher Dana Keener - San Jose CA
Gautam Ratilal Patel - San Jose CA
Assignee:

International Business Machines Corporation - Armonk NY
International Classification:

G11B 503
US Classification:

360 66, 3603241
Abstract:

The present invention provides a method and apparatus for performing automated spin valve combined pinned layer reset and hard bias initialization at the head gimbal assembly level. The reset combines a current pulse with an assisting magnetic field. The pinned layer reset and hard bias initialization is automated and performed by a single tool at the head gimbal assembly level to increase manufacturing throughput.

Yield/Quality Improvement Using Calculated Failure Rate Derived From Multiple Component Level Parameters
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US Patent:

6947871, Sep 20, 2005
Filed:

Sep 30, 2003
Appl. No.:

10/678031
Inventors:

Youping Deng - Sunnyvale CA, US
Christopher D. Keener - San Jose CA, US
Jinsong Wang - San Jose CA, US
Assignee:

Hitachi Global Storage Technologies Netherlands, B.V. - Amsterdam
International Classification:

G06F011/30
G21C017/00
US Classification:

702182
Abstract:

A method for improving yields in manufacturing processes includes identifying parameters which affect performance at a subsequent step in the process, collecting data concerning individual performance parameters, creating a reference scale which correlates individual parameters with probability of failure at a subsequent step in the process, testing a manufactured unit to collect performance data concerning two or more of the individual parameters from a manufactured unit, comparing performance data concerning two or more of the individual parameters from the manufactured unit to the reference scale to assign probability of failure for each of the single performance parameters, calculating a Figure of Merit, and utilizing the Figure of Merit to sort or disposition units.

Screening Test For Transverse Magnetic-Field Excited Noise In Giant Magnetoresistive Heads
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US Patent:

20030038626, Feb 27, 2003
Filed:

Aug 23, 2001
Appl. No.:

09/938436
Inventors:

Chris Carrington - Gonzales CA, US
Peter Fang - San Jose CA, US
Don Horne - Raymond WA, US
Christopher Keener - San Jose CA, US
Kenneth Mackay - San Jose CA, US
Assignee:

INTERNATIONAL BUSINESS MACHINES CORPORATION
International Classification:

G01R033/12
US Classification:

324/210000
Abstract:

A method and system for the rapid automatic screening of GMR heads for Barkhausen noise during production. This system rapidly and repeatedly measures associated noise in a GMR head subjected to a smoothly-varying external transverse magnetic field. The repeated Transverse Magnetic-field Excited Noise (TMEN) measurements are automatically sorted into bins to form a histogram, which is then automatically evaluated to develop TMEN range and weighted sum measures, which are then compared with predetermined standards for automatic acceptance or rejection of the GMR head under test. The GMR sensor Barkhausen noise is quantified through the use of a bandpass filter to remove all direct sensor responses, leaving only the noise signals, which are then repeatedly sampled to develop valid statistical Barkhausen noise measures suitable for automated analysis.