Paper 116

Just Enough Database for Manufacturing Yield Analysis

Robert A. Rutledge, Linda H. Tai, Garth W. Helf IBM Storage Systems Division, San Jose, CA

ABSTRACT

The IBM Storage Systems Division operatesadvanced manufacturing facilities for fabricating,assembling and testing all of the major componentsof IBM data storage products, from disks andmagneto-resistive heads through finished disk drivesand storage subsystems. The operational data fromour manufacturing sites are also used forengineering analysis, yield management andproblem diagnosis, within each factory and acrossfactories throughout the division. This cross-functional data allows us to exploit the benefit ofvertical integration by analyzing the relationshipsbetween hard drive performance and componentmeasurements, and using the resulting insight toeliminate yield detractors and optimize theperformance and quality of the finished product.However, the data association task is very time-consuming because the operational data are locatedin several different databases, and the logicalrelationships among databases is quite complex.

The JED (Just Enough Database) project wasundertaken to optimize our use of operational datafor yield analysis. The JED system consists of a DataWarehouse which combines and correlates datafrom several operational databases, and a graphicaluser interface, which automates the yield analysisprocess by providing engineers with preprogrammedfailure mapping and yield sensitivity curves and drill-down access to source data for in-depth interactiveanalysis. The user interface was written in SAS/AF®,to run on the SAS system for PCs, usingSAS/CONNECT® to extract data and code from theRS/6000® server. It has since been ported to run ona web browser using SAS/INTRNET®

INTRODUCTION

The disk drive industry is characterized by the rapidintroduction of advanced technology that deliversever higher capacity and performance for the endusers. The industry is also highly competitive, whichleads to continuous erosion of prices. In thisenvironment there is a significant advantage to beingable to ramp new products to high volume quickly

and take advantage of the higher profit margins onleading-edge products. Fast ramp to volume requiresfast yield learning to detect, diagnose and correct theinevitable problems that arise in new technology. TheIBM Storage Products Division manufactures themajor drive components and subassemblies as wellas the finished disk drive. This vertical integrationleads to close cooperation among the componentand drive development and manufacturing teams. Inparticular, we can access the various operationaldatabases to quantify the relationship of driveperformance to component measurements, and usethe resulting information to discover the root cause ofdrive problems, and optimize the specifications on in-line component measurements.

Figure 1: JED Analysis Objectives

However, the data association task is very timeconsuming because the operational data are locatedin several different databases, and the logicalrelationships among databases is quite complex.Drives which fail early in the assembly process dueto a bad component will be reworked and thenreassembled with new components. Therefore thereis not a one-to-one relationship between a drive andits components, and every query must use not onlyserial numbers, but also the time stamps of variousprocess steps, to insure that a particular component

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was in fact in the drive at the time of a specific test.The JED (Just Enough Database) project wasundertaken to optimize our use of operational datafor yield control. The first step was the creation of aData Warehouse, which brings together theoperational data from our Wafer, Disk, Head GimbalAssembly (HGA), Head Stack Assembly (HSA) andHard Disk Drive (HDD) factories. The next step wasthe creation of a user interface to make the datamore easily available and to automate some of thecommonly used yield analysis tools.

JED DATA WAREHOUSE

The JED Data Warehouse is a DB2 database ofapproximately 50 Gigabytes residing on an IBMRS/6000 server. It is updated weekly by extractingthe drive test results and parametric measurementsfor the previous week’s production from theoperational databases for our drive assembly plantsin San Jose and Singapore. After the drive serialnumbers and process time stamps are stored, wesearch our subassembly and component databasesto find the key in-line measurements, which are thenstored in JED for easy access. Before the data arestored, the drive and component data are pre-correlated so that one simple query will retrieve drivetest results along with measurements taken in thecomponent factory on the same parts. Thus the useris spared the difficulty of tracing component usagethrough the subassembly and drive assembly andrework processes.

Figure 2: JED Data Warehouse

As the term "Just Enough" suggests, we do notaggregate all of the available data, but only just

enough to satisfy our objective of fast and effectiveyield analysis. We select the drive test results thatare directly related to our yield calculations, and thein-line measurements that are likely to be informativefor yield and failure analysis. We further reduce thedata by capturing data on only a few thousandpassing and failing drives of each model each week.For a new product, this is a 100% sample, but as theproduct volumes increase, the sampling rate isgradually reduced to perhaps 5% of passing drivesand 50% of failing drives at each test station. Thereduced samples are more than enough for validdata analysis, but much more economical to update,store and analyze.

Users access the JED warehouse using the SASsystem for PCs running under OS/2 or Windows 95or NT. A typical user will run a PROC SQL with anODBC connection to extract data from JED, analyzeit, and then use PROC GPLOT or GCHART toproduce charts for presentation. The JED DataWarehouse has been in operation for more than ayear now, and has proven very effective in analyzingyield detractors in current and new products, andevaluating the effectiveness of proposed fixes.

However this system still left some bottlenecks in theinformation flow. There are many engineers who lackthe SAS programming skills to get at the data, andwho must therefore rely on a few experts to help outwith each request. Some common analysis routineswould get programmed many times as differentengineers made similar requests to different SASprogrammers. And a collection of static chartsbrought to a meeting for presentation usually led toquestions like “What if we don’t include the data fromlevel X components?", which could not be answeredwithout rerunning the analysis. We addressed all ofthese issues by constructing a user interface for JEDusing SAS/AF®.

SAS/AF USER INTERFACE FOR JED

The JED interface runs locally on the user’s PC,using SAS/AF code and SAS data sets which resideon the RS/6000 JED Data Mining server. The userstarts a small SAS/AF program on the PC, whichestablishes a SAS/CONNECT session with theserver, and downloads the main SAS/AF code. Thisinsures that the user is always accessing the latestversion of the SAS/AF code. The data used by theapplication are stored in two tiers of SAS data sets.The first tier is produced by running weekly SAS SQLprograms against the main JED data warehouse.These relatively large data sets, perhaps 500 MB per

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week, are then reduced to a second tier of summarydata sets, which contain enough information to drivethe SAS/AF interface. The reduced data sets containonly about 20 MB of information altogether forseveral weeks of production, which can bedownloaded to the user’s PC, and allow the interfaceto run with very fast refresh times.

Figure 3: JED User Interfaces

The first JED frame offers the user three choices:‘Remote’, ‘Download’ or ‘Local’. If ‘Remote’ ischosen, the application will download data sets asrequired for each frame the user visits. The‘Download’ option will download all data sets at once,so that thereafter all processing is done locally. The‘Local’ option will run cause the application to runstand-alone on the PC, using whatever versions ofcode and data were most decently downloaded. Thisallows one to continue with analysis when the serveris unavailable or inconvenient to use, e.g. while usinga laptop to present data at a meeting.

Figure 4: First Frame of SAS/AF JED Interface

The JED user interface is designed to provide anOLAP-like system for yield analysis. It provides fastanswers to the most commonly asked yield analysisquestions with point-and-click simplicity. Some of themore important analyses available are failure mapsand yield sensitivity curves. The failure mappingfunctions allow the user to detect failure trendsassociated with the type or source of componentsused, the head position in the drive, or the location ofheads on the parent wafer. The yield sensitivitycurves show the drive failure rate as a function of in-line measurements.

Figure 5 shows a frame that is used to explore thefailure rates for various error codes. The list boxesat right, which are automatically populated by SCLcode, allow the user to select the component typesand manufacturing sites and weeks of interest.These selections are used to reduce the summarydata sets to the data of interest, and then thecorresponding error rates are computed and plotted.

Figure 5: Failure Rates by Error Code

After the main yield detractors are identifiedby the frame shown in Figure 5, the user can select

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diagnostic charts that will point toward the root causeof the problem. One important type of plot is a wafermap showing which part of the wafer the failingheads came from. Figure 6 shows an example ofsuch a wafer map which indicates that heads fromthe upper right hand area of the wafer are moresusceptible to failing for the particular error codeplotted.

Figure 6: Wafer Map for Error Mode 1

Figures 7 and 8 show the distribution of waferlocation and head stack position for another specificerror code. The uniformity of the wafer plot, and thebias in the head stack distribution, strongly suggestthat the root cause for this problem will be found inthe HDD assembly process rather than the waferprocess.

Figure 7: Wafer Map for Error Mode 2

Figure 8: Head Positions for Error Mode 2

These error mapping charts provide valuableindicators of the root cause of each HDD yielddetractor, and what actions we might take toeliminate them.

This interface gives the user instant access to manymore charts than we could have possibly producedas static charts. A single SAS/AF frame allows theuser to quickly and dynamically produce error mapsdepending on his selection of component type, drivemodel, error code, and week of production, frombillions of possible combinations. Each frame thatcontains a chart also has a button that can bepressed to invoke SAS/INSIGHT®. This not onlybrings up the raw data, but also allows the user toexploit the full interactive graphic capability ofSAS/INSIGHT to explore the data.

Figure 9: Yield Sensitivity Plot

Figure 9 shows an example of another powerful JEDdiagnostic chart. This shows the cumulative failurerate over five HDD assembly and test processes as afunction of a parametric measurement on onecomponent in the drive. The chart is assembled froma large set of tables produced by PROC MEANS,

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with each table containing a sensitivity curve basedon a limited slice of the data, e.g. one week, one test,one site, etc. After the user selects the data region ofinterest from the list boxes at right, SAS macros areused to assemble the final cumulative charts fromthe individual tables.

From such charts we can easily see whichcomponent specifications should be adjusted tooptimize the HDD yield, and how much yieldimprovement we can expect to see from the newspecifications.

SAS/INTRNET USER INTERFACE FOR JED

The SAS/AF interface described above requiresinstallation of the SAS system for PCs as well as theinitial start-up SAS/AF application. Most of theengineers on site who are doing data analysis arealready using SAS, so this is not a problem.However, we also want to make the JED analysesavailable to a wider community, including managerswho are not SAS users, and engineers in our plantsin Singapore, Japan, Ireland, Germany and Mexico.The ideal way to accomplish this was by porting theJED interface to SAS/INTRNET, which makes iteasily available to anyone in IBM who has a PC, abrowser, and access to the IBM Intranet.

Figure 10: The JED Web Site

The SAS/INTRNET interface for JED wasprogrammed to run off the same data sets createdfor the SAS/AF interface. (See Figure 3.) Some re-programming was required to convert SAS/AFframes to HTML pages, but the SAS macros whichwere written to do the data manipulation and analysiswork for the SAS/AF interface could be reused forSAS/INTRNET with little or no changes. Figure 11shows how the Error Rate plot of Figure 5 lookswhen translated into the SAS/INTRNET interface for

JED.

Figure 11: Error Rates in the SAS/INTRNETinterface

THE NEXT STEPS

We will continue to improve the JED interface byadding new charting and analysis capabilities as wediscover new ways to diagnose yield problems andevaluate yield enhancements. This effort will includethe use of advanced data mining tools to explore themulti-dimensional relationships among parametricand logistic data and HDD yield. We have installedSAS Enterprise Miner® and IBM Intelligent Miner®on the Jed Data Mining server, and the preliminaryresults using the decision tree algorithms are verypromising.

We also plan to take advantage of SAS Version 7and SAS/WEBAF® when they are available toimprove the look, feel and functionality of the JEDinterface. And we will investigate the possible use ofSAS/MDDB®, which may be a more efficient way toaccomplish much of what we are currently doing withPROC MEANS and macros.

CONCLUSION

A key ingredient in time-to-volume manufacturing isthe rapid diagnosis and elimination of yielddetractors. The JED data warehouse, which bringstogether the operational data from our componentfabrication and hard drive assembly factories, isproving very effective for fast yield analysis of IBM'sserver class hard drive products. The JED SAS/AFand SAS/INTRNET user interfaces make the systemeven more effective by making the data and analysisalgorithms quickly and easily available to engineersthroughout the division. The use of these systems

Data Warehousing

over the past year has enabled us to quicklydiagnose several yield problems, propose solutionsto increase HDD yield, and evaluate in advance theeffect of the proposed fixes.

ACKNOWLEDGMENTS

The authors would like to express their appreciationto the many people who contributed to the successof the JED project:

The JED Steering Committee, including the authorsplus: Roger Brown, Randy Edelmaier, FranciscoInfante, Benny Lopez, Faye Ly, Ray Matsuoka, PatMotheral, Gan Qiu, Rainer Richter, Rick Spanel andRen Umeda.

The IBM Global Services Team who built andcontinue to maintain the JED Data Warehouse:Roger Buland, Kerry Hayes, Joe Huchel, MikeHenningsen, Bob Larocca, Barbara Okimoto, RobStrong.

Heidi Leung, also of IBM Global Services, who builtand maintains the JED Data Mining Server and theJED Web Site.

Qin Pan, with Ciber Information Services, for helpwith programming the JED Web interface.

John Balas of the IBM Microelectronics Division,whose DataView Application was the inspiration forthe JED SAS/AF interface.

Chuck Bininger of Trilogy Consulting Corp. who didan excellent job of designing SAS/AF frames forconstructing and submitting DB2 queries to the JEDData Warehouse.

Andy Norton and Jack Fuller, also of Trilogy, whospent many hours helping us to understand theconfusing maze of options for implementing a userinterface using SAS/AF, SAS/CONNECT,SAS/INTRNET and Java.

Art Carpenter of California Occidental Consultantsfor helpful discussions on SAS graphics and macros,and for raising the level of SAS competence at oursite through his classes and books.

The many SAS employees who were extremelyhelpful in getting us up and running with SASproducts in less time than we would have thoughtpossible, including:

- Kim Fields and Greg Lloyd (SAS San Jose Office)- Jim Georges (SAS Enterprise Miner)- Rena Soffir and Aaron Hill (SAS/INTRNET)- Sam Atassi and Margo Scharer (SAS/INTRNET)- Regina Louie and Jim Luther (SAS/CONNECT)

Irene Rutledge, for design of the JED-eye logo.

CONTACT INFORMATION

Your comments and questions are valued andencouraged. Contact the authors at:

Robert A. RutledgeIBM Storage Systems Division5600 Cottle RoadSan Jose, CA 95193Work Phone: (408) 256-0804Fax: (408) 256-2138Email: brutledg@us.ibm.com

Linda H. TaiIBM Storage Systems Division5600 Cottle RoadSan Jose, CA 95193Work Phone: (408) 256-6945Fax: (408) 256-8987Email: ltai@us.ibm.com

Garth W. HelfIBM Storage Systems Division5600 Cottle RoadSan Jose, CA 95193Work Phone: (408) 256-7514Fax: (408) 256-2410Email: helf@us.ibm.com

SAS, SAS/AF, SAS/CONNECT, SAS/INSIGHT,SAS/INTRNET, SAS/MDDB and SAS EnterpriseMiner are registered trademarks of SAS Institute Inc.in the USA and other countries. IBM, OS/2, DB2 andIntelligent Miner are registered trademarks ofInternational Business Machines Corporation. ®indicates USA registration.

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