System and method for early disc drive fault detection

• US 5,737,519 A
• Filed: 08/22/1995
• Issued: 04/07/1998
• Est. Priority Date: 08/22/1995
• Status: Expired due to Fees

• Current Assignee: Seagate Technology LLC (Seagate Technology Holdings Plc)
• Original Assignee: Seagate Technology plc (Seagate Technology Holdings Plc)
• Inventors: Chandler, Horace David, Abdelnour, Ghassan Maurice, Rogers, Steven Hill
• Primary Examiner(s): CHUNG, PHUNG M
• Application Number:
  US08/518,105
• Time in Patent Office: 959 Days
• Field of Search: 371/5.1, 371/26, 371/25.1, 371/67.1, 371/5.5, 360/97.01, 395/183.15, 395/183.13, 395/183.02
• US Class Current: 714/39
• CPC Class Codes: G11B 19/04 Arrangements for preventing, inhibiting, or warning against double recording on the same blank or against other recording or reproducing malfunctions
• CPC Class Codes: G11B 20/182 using test patterns
• CPC Class Codes: G11B 33/10 Indicating arrangements; Warning arrangements G11B15/04, G11B19/04, G11B27/34, G11B27/36 take precedence
• CPC Class Codes: G11B 5/4806 specially adapted for disk drive assemblies, e.g. assembly prior to operation, hard or flexible disk drives G11B5/488 - G11B5/54 take precedence

Abstract

Apparatus and method for the early detection of faults in a head-disc assembly (HDA) from a disc drive manufacturing process. Parametrics are obtained from an HDA at a parametric station and provided to a pattern recognition system for estimating an error rate category from the measured HDA parametrics. The estimated error rate category and the parametrics are provided to a fuzzy inferencing system, which uses linguistic rules to classify the HDA as GOOD, MARGINAL or BAD, based upon the parametrics and the estimated error rate category. HDAs classified as GOOD or MARGINAL continue processing through dynamic burn-in (DBI), while HDAs classified as BAD are subjected to rework. The pattern recognition system includes a reference database containing historical parametric and associated error rate data, which is updated over time by the subsequent inclusion of selected parametrics and measured error rates for HDAs subjected to DBI.

Claims

1. An apparatus for early detection of faults in a device under test comprising:

(a) means for obtaining parametrics for a device under test;

(b) means for providing a database of historical parametric patterns and corresponding error rates;

(c) means for determining a similarity measure for each historical parametric pattern by comparison of the historical parametrics to the parametrics;

(d) means for estimating an error rate for the device from the corresponding error rates of a selected number of historical parametric patterns;

(e) means for providing a set of linguistic rules;

(f) means for applying the linguistic rules to the set of fuzzy linguistic domains for the estimated error rate and parametrics to give a classification of the device; and

(g) means for dispositioning the device for further operations according to the classification of the device.

2. An apparatus for early detection of faults in a disc drive head-disc assembly, comprising:

(a) means for obtaining head-disc assembly parametrics;

(b) means for providing a database of historical parametric patterns and corresponding error rate information;

(c) means for determining a measure of the similarity of each historical parametric pattern to the head-disc assembly parametrics;

(d) means for estimating an error rate category for the head-disc assembly from the corresponding error rate information of a selected number of the most similar historical parametric patterns;

(e) means for determining the membership of the estimated error rate category and each of the head-disc assembly parametrics in a set of fuzzy linguistic domains;

(f) means for providing a set of linguistic rules;

(g) means for applying the linguistic rules to the set of fuzzy linguistic domains for the estimated error rate category and head-disc assembly parametrics to give a classification of the head-disc assembly; and

(h) means for dispositioning the head-disc assembly for further operations according to the classification of the head-disc assembly.

3. A method for early detection of faults in a device under test comprising the steps of:

(a) obtaining parametrics for a device under test;

(b) providing a database of historical parametric patterns and corresponding error rates;

(c) determining a similarity measure for each historical parametric pattern by comparison of the historical parametrics to the parametrics;

(d) estimating an error rate for the device from the corresponding error rates of a selected number of historical parametric patterns;

(e) providing a set of linguistic rules;

(f) applying the linguistic rules to the set of fuzzy linguistic domains for the estimated error rate and parametrics to give a classification of the device; and

(g) dispositioning the device for further operations according to the classification of the device.

4. A method for early detection of faults in a disc drive head-disc assembly, comprising:

(a) obtaining head-disc assembly parametrics;

(b) providing a database of historical parametric patterns and corresponding error rate information;

(c) determining a measure of the similarity of each historical parametric pattern to the head-disc assembly parametrics;

(d) estimating an error rate category for the head-disc assembly from the corresponding error rate information of a selected number of the most similar historical parametric patterns;

(e) determining the membership of the estimated error rate category and each of the head-disc assembly parametrics in a set of fuzzy linguistic domains;

(f) providing a set of linguistic rules;

(g) applying the linguistic rules to the set of fuzzy linguistic domains for the estimated error rate category and head-disc assembly parametrics to give a classification of the head-disc assembly; and

(h) dispositioning the head-disc assembly for further operations according to the classification of the head-disc assembly.

5. An apparatus for early detection of faults in a disc drive head-disc assembly, comprising:

measurement means for obtaining parametrics from a head-disc assembly;

pattern recognition means, responsive to the measurement means, for estimating an error rate category for the head-disc assembly from the parametrics, the pattern recognition means comprising;

a reference database comprising a plurality of records, said records including historical parametric data and associated error rates;

similarity measure means, responsive to the reference database, for determining a similarity measure for each of the plurality of records in the reference database, each similarity measure providing a measure of the similarity between the parametrics and the historical parametric data in each record;

selection means, responsive to the reference database and the similarity measure means, for selecting a predetermined number of records from the reference database in accordance with the similarity measures determined by the similarity measure means; and

error rate estimation means, responsive to the reference database and the selection means, for estimating the error rate category of the head-disc assembly; and

fuzzy inferencing means, operably connected to the pattern recognition means, for classifying the head-disc assembly for further dispositioning.

6. A method for early detection of faults in a disc drive head-disc assembly comprising the steps of:

obtaining parametrics for a head-disc assembly;

providing an estimated error rate for the head-disc assembly, comprising the steps of;

providing a reference database comprising a plurality of records, said records including historical parametric data and associated error rates;

determining a similarity measure for each of the records in the reference database; and

using selected records to provide the estimated error rate; and

using the parametrics and the estimated error rate to classify the head-disc assembly for further dispositioning.

7. The method of claim 6, wherein the step of using the parametrics and the estimated error rate to classify the head-disc assembly for further dispositioning comprise the steps of:

providing a set of linguistic rules;

fuzzifying the parametrics and the estimated error rate; and

applying the linguistic rules to the fuzzified parametrics and estimated error rate to classify the head-disc assembly.