The present invention relates generally to processes for testing media disks, and more specifically, to methods for testing for defects on magnetic media storage disks.
In the manufacture and assembly of magnetic media storage disks for storage drives (e.g., hard drives), a number of disk defects are commonly found. These defects may require debugging that can be both time consuming and expensive to perform. A failed disk of this sort will often have to be removed from a failed drive and subjected to media certification or testing to determine if the magnetic disk is usable or not. The media certification determines the number of defect counts in a given washer shaped area of the disk. If the number exceeds a predetermined threshold, then the magnetic disk is put aside for further processing. If the number falls below the predetermined threshold, then the magnetic disk is recycled into the hard disk drive manufacturing process.
A media test tool such as the MC900 (media certifier 900 series) can be used to perform the media certification. However, a known short-coming of this tool and other such tools in the industry is the ability to detect spiral/circular scratches and light micro scratches. As such, an alternative method for detecting and screening out such defects is needed.
Pattern recognition is an established science that is sometimes applied to detecting defects on media. Pattern recognition employs complex mathematical modeling to perform feature extraction, feature recognition and then assimilation of the results for final classification. While aspects of pattern recognition are relatively well established, it is believed that such techniques have not been successfully applied to address the detection of a number of defect types including both light micro scratches and spiral/circular scratches.
Aspects of the invention relate to methods for testing for defects on magnetic media storage disks. In one embodiment, the invention relates to a method for testing for defects in magnetic media storage disks, the method including dividing a surface of a magnetic media disk into a plurality of radial zones, dividing the disk surface into a plurality of concentric zones, thereby forming a preselected number (N) of wedge subsections for each of the concentric zones, scanning the disk surface for defects, counting the defects contained within each of the wedge subsections, summing the defects contained within two or more of the wedge subsections, comparing the summed defects with a preselected threshold, and determining, based on the comparison, a defect type of the disk.
a is a polar plot of light micro scratches on a media disk having the scratches roughly concentrated on opposite sides of the disk thereby illustrating two pole or LMS-2 type defects in accordance with one embodiment of the invention.
b is a rectangular plot of the light micro scratches on the media disk of
a is a polar plot of light micro scratches on a media disk having the scratches roughly concentrated on four areas of the disk thereby illustrating four pole or LMS-4 type defects in accordance with one embodiment of the invention.
b is a rectangular plot of the light micro scratches on the media disk of
The characterization of defects in magnetic media can be important and fairly application specific. With this in mind a discussion of a number of preselected ways for characterizing defects is believed to be helpful.
a is a polar plot of light micro scratches on a media disk having the scratches roughly concentrated on opposite sides of the disk thereby illustrating two pole or LMS-2 type defects in accordance with one embodiment of the invention. If the polar plot is extrapolated to a rectangular plot, the defects are illustrated as being in two relatively distinct groups.
a is a polar plot of light micro scratches on a media disk having the scratches roughly concentrated on four areas of the disk thereby illustrating four pole or LMS-4 type defects in accordance with one embodiment of the invention. The density or concentration of the defects displayed on the disk illustrate the pattern of four poles that are roughly evenly spaced apart.
As can be extrapolated from
Referring now to
The process then scans (106) the disk surface for defects. In one embodiment, the process performs one or more tone scans and/or other suitable scans known in the art. The process counts (108) the defects contained within each of the wedge subsections. The process then sums (110) the defects contained within two or more of the wedge subsections. In several embodiments, the wedge subsections that are summed vary in accordance with the type of defect to be detected. The process compares (112) the summed defects with one or more preselected thresholds. In a number of embodiments, the preselected thresholds are determined based on the results of empirical testing. The process then determines (114), based on the comparison, a defect type of the disk. In some cases there may be no defect. In other cases, the defect types can include a LMS-2 type defect, a LMS-4 type defect, a LMS-6 type defect, a marking/non-uniform type defect, a spiral/circular scratch type defect, and/or combinations of these or other known defect types. Based on the classification of the defect, the defective disks can be identified quickly and reworked efficiently to address the specific defect.
In one embodiment, the process can perform the sequence of actions in a different order. In another embodiment, the process can skip one or more of the actions. In other embodiments, one or more of the actions are performed simultaneously. In some embodiments, additional actions can be performed.
The algorithm first sums (202) the defects found in the first two wedge sections (W1, W2) and determines whether the sum is greater than 5,000. The algorithm then sums (204) the defects found in the second two wedge sections (W3, W4) and determines whether the sum is less than 1,000. The algorithm then determines (206) whether both such conditions are true, and, if so, stores information indicative of a LMS-2 type defect having been found on the disk. In the algorithm, preselected defect thresholds of 1,000 and 5,000 are used. In other embodiments, other suitable thresholds can be used.
The process then determines (304) whether the expression “Sum[W(I), W(I+1)]>5,000 AND Sum[W(I+2), W(I+3)]<1000” is true. The former being a comparison of the sum of defects for wedge subsections W(I) and W(I+1) and a first preselected defect threshold of 5,000. The latter being a comparison of the sum of defects for wedge subsections W(I+2) and W(I+3) and a second preselected defect threshold of 1,000. If the expression is true, then the process has detected (306) a LMS-2 type defect. If the expression is false, then the process determines (308) whether all of the wedge subsections have been counted by examining the expression “I+3=N”. If all of the wedge subsections have been counted, then the process notes (310) that no LMS-2 type defects were found. If all of the wedge subsections have not been counted, the process increments (312) the index variable I and returns to determining (304) the sum expression for the next group of wedge subsections.
In one embodiment, the process can perform the sequence of actions in a different order. In another embodiment, the process can skip one or more of the actions. In other embodiments, one or more of the actions are performed simultaneously. In some embodiments, additional actions can be performed.
The process then determines (504) whether the expression “Sum[W(I), W(I+2)]>5,000 AND Sum[W(I+1), W(I+3)]<1000” is true. The former being a comparison of the sum of defects for wedge subsections W(I) and W(I+2) and a first preselected defect threshold of 5,000. The latter being a comparison of the sum of defects for wedge subsections W(I+1) and W(I+3) and a second preselected defect threshold of 1,000. If the expression is true, then the process has detected (506) a LMS-4 type defect. If the expression is false, then the process determines (508) whether all of the wedge subsections have been counted by examining the expression “I+3=N”. If all of the wedge subsections have been counted, then the process notes (510) that no LMS-4 type defects were found. If all of the wedge subsections have not been counted, the process increments (512) the index variable I and returns to determining (504) the sum expression for the next group of wedge subsections.
In one embodiment, the process can perform the sequence of actions in a different order. In another embodiment, the process can skip one or more of the actions. In other embodiments, one or more of the actions are performed simultaneously. In some embodiments, additional actions can be performed.
The process then determines (604) whether the expression “Sum[W(I), W(I+2)]>5,000 AND Sum[W(I+1), W(I+3)]<3000” is true. The former being a comparison of the sum of defects for wedge subsections W(I) and W(I+2) and a first preselected defect threshold of 5,000. The latter being a comparison of the sum of defects for wedge subsections W(I+1) and W(I+3) and a second preselected defect threshold of 3,000. If the expression is true, then the process has detected (606) a LMS-6 type defect. If the expression is false, then the process determines (608) whether all of the wedge subsections have been counted by examining the expression “I+3=N”. If all of the wedge subsections have been counted, then the process notes (610) that no LMS-6 type defects were found. If all of the wedge subsections have not been counted, the process increments (612) the index variable I and returns to determining (604) the sum expression for the next group of wedge subsections.
In one embodiment, the process can perform the sequence of actions in a different order. In another embodiment, the process can skip one or more of the actions. In other embodiments, one or more of the actions are performed simultaneously. In some embodiments, additional actions can be performed.
The process then determines (704) whether the expression “Sum[W(I), W(I+1)]>5,000 AND Sum[W(I+2), W(I+3), . . . ,W(N)]<3000” is true. The former being a comparison of the sum of defects for wedge subsections W(I) and W(I+1) and a first preselected defect threshold of 5,000. The latter being a comparison of the sum of defects for all wedge subsections except the first two and a second preselected defect threshold of 3,000. If the expression is true, then the process has detected (706) a marking/non-uniform type defect. If the expression is false, then the process notes (708) that no LMS-6 type defects were found.
In another embodiment, the process 700 can continue in order to detect whether a spiral or circular type defect exists. In such case, the process 700 would continue from block 708 where it was determined that no LMS-2, LMS-4, LMS-6, or marking type defects were found and determine whether a new sum expression of “Sum[W(1),W(2),W(3),W(4),W(5),W(6)]>3,000 OR Sum[W(3),W(4),W(5),W(6),W(7),W(8)]>3,000 OR Sum[W(5),W(6),W(7),W(8), W(9)]>3,000” is true. If the new sum expression is true, then the process has detected a spiral or circular type defect (e.g., ring defect). If the expression is false, then the process notes that no spiral/circular type defects were found.
In one embodiment, the process can perform the sequence of actions in a different order. In another embodiment, the process can skip one or more of the actions. In other embodiments, one or more of the actions are performed simultaneously. In some embodiments, additional actions can be performed.
While the above description contains many specific embodiments of the invention, these should not be construed as limitations on the scope of the invention, but rather as examples of specific embodiments thereof. Accordingly, the scope of the invention should be determined not by the embodiments illustrated, but by the appended claims and their equivalents.
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