PUBLICATIONS

NIST Special Publication 500-200

Computer

Systems

Technology

U.S. DEPARTMENT OF

COMMERCE

Technology Administration

National Institute of Standards and Technology

Nisr NAT L INST OF STAND & TECH R.I.C,

Development of a Testing

Methodology to Predict Optical

Disk Life Expectancy Values

Fernando L. Podio

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NIST Special Publication 500-200

Development of a Testing

Methodology to Predict Optical

Disk Life Expectancy Values

Fernando L Podio

Advanced Systems Division

Computer Systems Laboratory

National Institute of Standards and Technology

Technology Administration

Gaithersburg, MD 20899

December 1991

Sponsored by:

U.S. National Archives and Records Administration (NARA)

Washington, DC 20408

U.S. DEPARTMENT OF COMMERCE

Robert A. Mosbacher, Secretary

Technology Administration

Robert M. White, Under Secretary for Technology

National Institute of Standards and Technology

John W. Lyons, Director
Reports on Computer Systems Technology

The National Institute of Standards and Technology (NIST) has a unique responsibility for computer

systems technology within the Federal government. NIST's Computer Systems Laboratory (CSL) develops standards and guidelines, provides technical assistance, and conducts research for computers and

related telecommunications systems to achieve more effective utilization of Federal information technology resources. CSL's responsibilities include development of technical, management, physical, and administrative standards and guidelines for the cost-effective security and privacy of sensitive unclassified

information processed in Federal computers. CSL assists agencies in developing security plans and in improving computer security awareness training. This Special Publication 500 series reports CSL re- search and guidelines to Federal agencies as well as to organizations in industry, government, and

academia.

National Institute of Standards and Technology Special Publication 500-200

Natl. Inst. Stand. Technol. Spec. Publ. 500-200, 96 pages (Dec. 1991)

CODEN: NSPUE2

U.S. GOVERNMENT PRINTING OFFICE

WASHINGTON: 1991

For sale by the Superintendent of Documents, U.S. Government Printing Office, Washington, DC 20402
Disclaimer

This publication illustrates the development of a testing methodology that can be applied

to predict optical disk life expectancy values. The work was not aimed towards evaluating a particular type of optical disk. Commercially available optical disks have been used for

the tests with the sole intent of illustrating the test procedures implemented. Values

obtained showing changes in media parameters are included. Life expectancy values

derived from the experiments are also shown to illustrate the testing approach rather than as an indication of the actual life expectancy of the type of disks used in the experiments.

The reasons for this include the use of a very small number of samples with respect to the

population of disks in existence, the presence of other degradation effects which do not

correspond to the prediction model, and the use of stress environments with higher than

normal relative humidity levels to permit aging disks in a reasonable length of time.

Because of the nature of this report, it is necessary to mention vendors and commercial

products. The presence or absence of a particular trade name product does not imply

criticism or endorsement by the National Institute of Standards and Technology, nor does

it imply that the products identified are necessarily the best available for the purpose.

iii

Acknowledgments

Many people, in addition to the author, have contributed to the program outlined in this

publication, and the author is most appreciative of that assistance. Thanks are due to

Remigius Onyshczak from NISTfor his participation on the blank reflectance measurement

and the development of a PC-based multi-oven controller to maintain aging environments

using saturated salt solutions. Eduardo Sanchez Villagran, a guest scientist from

Argentina, is also thanked for his participation in the design of the data acquisition and

byte error rate (BER) analysis system. Mr. Onyshczak and Mr. Sanchez Villagran are also

thanked for their participation in writing an earlier progress report to the sponsor on the

same program in September 1989. Since then, the work has been revised, but some of

their thoughts are still included in this report.

The author very much appreciates the help of Mark Williamson of the NIST staff and Gill Hadar, a guest scientist from Israel, for revising the statistical analysis used in this work.

Appreciation is also extended to Dr. James J. Filiben from NIST for his useful advice on

statistical analysis, Wayne Nelson, currently a senior research fellow at NIST, for his useful

advise on applied life data analysis, and Dr. Santos Mayo for his useful advise on

accelerated aging testing. Particular thanks are due to Lloyd Gilmore of NIST for his help

in many areas of the program of work and for performing many of the tests.

Special thanks are due to the following individuals from NIST: Dana Grubb (manager. Data

Storage Media Group), Tom Bagg, Natalie Willman, and Magaly Lenker; and the previous

coop-student John Gorczyca. Appreciation is also due to two previous guest scientists

from China: Dr. Lu Da and Zhiping Zhou. The author appreciates useful technical

discussions with members of different voluntary industry standards committee members

related with this work. Special thanks are given to members of Technical Committee

X3B11, Optical Digital Data Disks, and the Joint Technical Commission on Data

Permanence.

The technical support provided by teams of engineers from the Sony Company and ATG

Gigadisc is very much appreciated. Also appreciated are the contributions in equipment

to this program by these companies. Sony contributed to this program equipment

equivalent to approximately $50,000. ATG has contributed equipment equivalent to $5,000.

V

Executive Summary

The National Institute of Standards and Technology (NIST), with the partial sponsorship of

the U.S. National Archives and Records Administration (NARA), has set up an optical

media measurement laboratory to test and analyze optical disk media characteristics and

develop a testing methodology that can be used for deriving life expectancy values for

optical disks.

The methodology included determining the characteristics that define the media end of life, a means of measuring the selected parameters, and a means of accelerating the media

aging. Byte error rate (BER) was selected as the quality parameter and an end of life for

the BER of 5 X 10'^ was also adopted. This value was a typical number used by the

manufacturers at the time of the beginning of this program. The BER was measured over samples of three areas of the disks (inner, middle, and outer) and using three different

patterns (high frequency, sequential, and random). Three environments were used for

accelerating the aging of the media: 80 °C, 90% relative humidity (RH); 70 °C, 90% RH;

and 60 ° C, 90% RH. The reflectance of the blank areas and the carrier-to-noise ratio were

also measured to monitor their behavior before and after the aging tests.

To illustrate the use of the testing methodology, the accelerated aging tests were run on

a small set of polycarbonate substrate media. The particular type of media used was

recommended by NARA. BER values were estimated from measurements in three areas

of the disks and from sectors written with three different patterns. Extrapolated life expectancy values for room temperature and the same relative humidity used for the stress

environments were then estimated from modified Arrhenius plots for each of the patterns

and areas used for the BER measurements.

The results indicate that the methodology applied to a small sample of disks yields a range

of extrapolated life expectancv values depending upon the patterns and areas used for the

BER measurement. These results include data taken in areas of the disks where

secondary effects took place. These secondary effects were due to causes such as damage to the sealing on the outer and inner edges of the disk due to the stress

conditions that may have allowed moisture to seep in and the handling of the disks. These

secondary effects cannot be accommodated by the mathematical model used for the

extrapolations.

Another approach was also used to represent the results. This approach selected the

data derived only from the middle area (assuming that these areas of the disks were the

more isolated from the secondary effects) and from sectors written only with the high

vii
frequency pattern (worst case pattern for this implementation). Using tliese more

representative data (high frequency pattern in the middle area) and median values of the

BER, an extrapolated life expectancy of 121 years at room temperature and 90% RH was

derived. Using the upper 95% confidence limit of the BER for the extrapolations, a more

conservative extrapolated life expectancy value of 57 years at room temperature and 90%

RH was obtained. However, assuming a maximum RH range for a storage environment

of 40% to 50% RH, the projected life expectancy values using this method should be

longer than the ones derived from our experiments.

These results are an approximation and should be used with caution because the

experiments used a small number of samples and the presence of degradation effects

which do not correspond to the prediction model. Furthermore, it should be noted that

the higher than normal humidity levels used to permit aging disks in a reasonable length

of time influences the results.

The most important conclusion of this work is that extrapolated life expectancy values may

vary greatly because they depend, among other factors, on the test method used for

calculating the guality parameter (e.g.. BER). the measurement approach including data

patterns used, areas measured (e.g.. middle area), amount of data tested, mathematical

mode! used, criteria for data analysis (including the statistical analysis used, confidence

intervals, etc), and the stress conditions. Therefore, prospective users should be aware

that claims of a life expectancy specification should be accompanied by specification of the

above factors. The results derived in this research indicate that different testing methods

have the potential for deriving different values of extrapolated life expectancy, all of which

may be valid. The need for standard test methods for life expectancy is apparent. These

standards would provide a commonly agreed upon basis for life expectancy testing so that

vendor claims can be properly assessed by prospective users. Otherwise, comparisons

between different products will not be possible.

New developments in both write-once read many times (WORM) and rewritable media

technology warrant further research in accelerated life testing of these media. Additional

research is needed to investigate on-line monitoring and reporting of error rate and error

distribution. This would provide data managers with needed information on the status of

their data. Research in the care and handling of these media and in test methods for

media characteristics is also needed. Work on standardization of life expectancy methods,

media interchange and test methods for media characteristics should continue.

This program of work also included active participation by NIST staff in standards

committees which are developing test methods for predicting life expectancy and test

methods for media characteristics. With NIST leadership, significant progress has been

achieved in Technical Committee X3B11, Optical Digital Data Disks for standardizing test

methods for media characteristics. The American National Standard Institute (ANSI) has

approved a test methods standard (ANSI X3.1 99-1 991 ) which documents test methods for

media characteristics for 356 mm WORM media. Similar standards for other type of media

are also being developed by TC X3B11. NIST is also working in the Joint Technical

Commission on Data Permanence in the standardization of life expectancy for optical disk

systems.

viii
Contents

Disclaimer iii

Acknowledgments v

Executive Summary vii

Abstract xv

1 Program Overview 1

1.1 History of the Program 1

1 .2 The Methodology 2

2 Experimental Procedures 7

2.1 Introduction 7

2.2 BER Measurements 8

2.2.1 Introduction 8

2.2.2 Measurement Procedure 9

2.2.3 Database Management 10

2.2.4 Initial Tests to Determine the Statistical Analysis 10

2.2.5 Determination of the Number of Bytes to Be

Used for the Test 11

2.2.6 Control Group of Disks 12

2.3 Blanl< Area Reflectance Measurement 12

2.3.1 Introduction 12

2.3.2 Measurement Procedure 12

2.4 Carrier-to-Noise Ratio 13

2.4.1 Introduction 13

2.4.2 Recording a Carrier on the Media 13

2.4.3 Reading From the Media 15

2.5 Accelerated Aging Tests 17

2.6 Visual Inspection of the Media and Defects Localization 18

ix
3 Results 21

3.1 Introduction 21

3.2 BER Results 21

3.3 Application of the Arrhenius Model to the Data 25

3.3.1 Practical Considerations in the Application of the

Arrhenius Model 25

r. 3.3.2 Extrapolated Results From Modified Arrhenius Plots 26

"

; 3.3.3 BER Control Charts for the Control Group 28

3.4 Optical Inspection of the Media 28

: 3.5 CNR Results . 29

3.6 Reflectance Measurement Results 29

4 Conclusions and Recommendations 77

4.1 Conclusions From the BER Results and the Extrapolations From the

Modified Arrhenius Plots 77

4.2 Discussion and Recommendations 79

4.3 Related Programs at NIST on Data Preservation 81

5 References 83

X
List of Figures

2.1 System interconnection 8

2.2 Grouping of sectors for the BER measurement 10

2.3 Statistical approacli for the BER measurement 11

2.4 Reflectance measurement setup 13

2.5 Generating a carrier on the media for disk drive 1 14

2.6 Generating a carrier on the media for disk drive 2 15

2.7 Amplitude versus frequency 16

2.8 CNR measurement setup for disk drive 1 16

2.9 CNR measurement setup for disk drive 2 17

2.10 Multi-oven controller 18

2.11 Opticalinspection system setup 19

3.1 BER versus aging time (sequential pattern) @ 60 " C, 90% RH 30

3.2 BER versus aging time (random pattern) @ 60 ° C, 90% RH 31

3.3 BER versus aging time (high frequency pattern) @ 60 ° C, 90% RH . . . 32

3.4.a-c BER versus aging time at 60 ° C, 90% RH for three patterns 33

3.5 BER versus aging time (inner area) @ 60 °C, 90% RH 34

3.6 BER versus aging time (middle area) @ 60°C, 90% RH 35

3.7 BER versus aging time (outer area) @ 60 ° C, 90% RH 36

3.8.a-c BER versus aging time at 60 ° C, 90% RH for three areas 37

3.9 BER versus aging time (middle area/

high frequency pattern) @ 60 ° C, 90% RH 38

3.10 BER versus aging time (sequential pattern) @ 70 °C, 90% RH 39

3.11 BER versus aging time (random pattern) @ 70 °C, 90% RH 40

3.12 BER versus aging time (high frequency pattern) @ 70 °C, 90% RH .. 41

3.13.a-c BER versus aging time at 70 °C, 90% RH for three patterns 42

3.14 BER versus aging time (inner area) @ 70 °C, 90% RH 43

3.15 BER versus aging time (middle area) @ 70 °C, 90% RH 44

3.16 BER versus aging time (outer area) @ 70 °C, 90% RH 45

3.17.a-c BER versus aging time at 70 °C, 90% RH for three areas 46

3.18 BER versus aging time (middle area/

high frequency pattern) @ 70 ° C, 90% RH 47

3.19 BER versus aging time (sequential pattern) @ 80 °C, 90% RH 48

3.20 BER versus aging time (random pattern) @ 80 ° C, 90% RH 49

3.21 BER versus aging time (high frequency pattern) @ 80 ° C, 90% RH . . . 50

3.22.a-c BER versus aging time at 80 ° C, 90% RH for three patterns 51

3.23 BER versus aging time (inner area) @ 80 ° C, 90% RH 52

3.24 BER versus aging time (middle area) @ 80 ° C, 90% RH 53

3.25 BER versus aging time (outer area) @ 80 °C, 90% RH . 54

xi
3.26.a-c BER versus aging time at 80 ° C, 90% RH for three areas .......... 55

3.27 BER versus aging time (middle area/

high frequency pattern) @ 80 ° C, 90% RH 56

3.28 Arrhenius plot for the BER (sequential pattern) 57

3.29 Arrhenius plot for the BER (random pattern) 58

3.30 Arrhenius plot for the BER (high frequency pattern) 59

3.31 .a-c Arrhenius plots for the BER (three patterns) 60

3.32 Arrhenius plot for the BER (inner area) 61

3.33 Arrhenius plot for the BER (middle area) 62

3.34 Arrhenius plot for the BER (outer area) . 63

3.35.a-c Arrhenius plots for the BER (three areas) 64

3.36 Arrhenius plot for the BER (middle area/

high frequency pattern) 65

3.37 Arrhenius plot for the BER (middle area/

high frequency pattern, upper 95% confidence limit) 66

3.38 BER values for the control group 67

3.39. a-c CNR versus aging time at 60 " C, 90% RH for three tracks 68

3.40. a-c CNR versus aging time at 70 °C, 90% RH for three tracks 69

3.41 .a-c CNR versus aging time at 80 ° C, 90% RH for three tracks 70

3.42.a-c CNR for the control group (three tracks) 71

3.43 Reflectance versus aging time for the

inner blank area, @ 60 ° C, 90% RH 72

3.44 Reflectance versus aging time for the

outer blank area, @ 60 ° C, 90% RH 72

3.45 Reflectance versus aging time for the

inner blank area, @ 70 °C, 90% RH 73

3.46 Reflectance versus aging time for the

outer blank area, @ 70 ° C, 90% RH 73

3.47 Reflectance versus aging time for the

inner blank area, @ 80 ° C, 90% RH 74

3.48 Reflectance versus aging time for the

outer blank area, @ 80 " C, 90% RH 74

3.49 Reflectance values for the control group

(inner blank area) 75

3.50 Reflectance values for the control group

(outer blank area) 75

xii
List of Tables

3.1 Stress environments of high temperature and humidity 21

3.2 Extrapolated EOL values (in hours) for three sets of disks

under three stress conditions 24

3.3 Extrapolated life expectancy values (in years) derived over

the inner, middle, and outer areas, using three different patterns 26

3.4 Extrapolated life expectancy values (in years) derived on three

independent areas, using three different patterns

(high frequency, random, and sequential) 27

3.5 Extrapolated EOL values (in hours) over the middle area 27

3.6 Extrapolated life expectancy values (in years) derived over

the middle area using the high frequency pattern 28

xiii

Development of a Testing Methodology to

Predict Optical Disk Life Expectancy Values

Fernando L. Podio

Abstract

There are no standards for longevity of optical disks that can assist managers in the

Federal government to select the right media for the storage of permanent records, and

to know how long the information may be safely stored on those disks. This report

focuses on research undertaken at the National Institute of Standards and Technology to

develop a methodology to predict optical disk life expectancy values. In this research

accelerated aging tests were run on small sets of disks and the quality parameter (the byte

error rate) was periodically measured between aging cycles. These tests were used with

a mathematical prediction model to develop a testing methodology.

This report presents the results obtained. The need for standard test methods for

predicting life expectancy and for measuring media characteristics is apparent. Life

expectancy extrapolations derived from the experiments produced a range of values

depending upon the method used for deriving the quality parameter. Recommendations

are made about the implementation of a testing methodology for life expectancy

predictions, and what information to include in a life expectancy specification.

Key words: accelerated aging; Arrhenius model; byte error rate; media lifetime; optical

disks, stress tests; optical disks, test methods.

XV

Chapter 1

Program Overview

1 .1 History of the Program

The National Institute of Standards and Technology (NIST) computer storage optical media

research program began several years ago with the recognition that an investigation into

the life expectancy properties of optical digital data disks was needed [1]. The current

NIST research program includes optical media stability studies, an optical media testing

laboratory, and studies related to the utilization of optical data storage. The U.S. National

Archives and Records Administration (NARA) sponsored research under this program

aimed at developing a testing methodology that can be used to predict optical disk life expectancy values. Participation in standardization efforts in methods for predicting life expectancy, recommended practices for data permanence, and test methods for media

characteristics were also goals of the program.

Under this program, NIST developed a methodology for deriving optical disk life expectancy values. NIST also formed an optical media measurement laboratory able to

test optical disk media characteristics and run accelerated aging tests on different types

of optical disks representing different media technologies, recording layer structures and

substrates. The results and conclusions of the program are being shared with the relevant

standards committees.

Another direct consequence of the program is the significant progress achieved in the last

two years in the development of standard test methods for media characteristics. With

NIST leadership. Technical Committee (TC) X3B1 1 Optical Digital Data Disks, is developing

standards for test methods for media characteristics. One standard was approved as an

American National Standard [2]. This standard includes test methods for media

characteristics for 356 mm write-once read many times (WORM) media. Other draft test

methods standards under development include test methods for media characteristics for

130 mm and 90 mm rewritable magneto-optic media and 130 mm WORM media.

The expertise developed by NIST staff also contributes to alternative programs for better

utilization of optical media by the Federal Government. NIST staff is chairing a NIST/NASA

Working Group for the development of test methods and specifications for 14 inch

rewritable ruggedized optical media (with the sponsorship of NASA). A NIST Special

Publication documents these test methods [3]. NIST staff is working in a program partially

sponsored by NARA to study the care and handling of optical media. NIST is also involved

1
in a program to investigate the status of on-line monitoring techniques for error rates and

error distributions on optical disk subsystems. Under this program the Computer Systems

Laboratory of NIST organized a government/industry working group to build an industry

consensus for a method(s) of reporting error rate information through an interface.

The future availability of devices to read current media depends on the existence of a

sufficiently large market with multiple vendors. This requires industrial standards for media

interchange. Otherwise, drives capable of reading the particular media and format may

become unavailable before the end of life of the media. Requirements for media

interchange standards based on only one format may be even more helpful in resolving

that problem. NIST is also actively working in national and international standardization

committees in the development of media interchange standards and it is also actively

participating in the IT9/AES Joint Technical Commission (JTC) on Data Permanence. The

work of the JTC will eventually lead to the standardization of methods to predict the life expectancy of optical computer storage media/systems. The expertise acquired by NIST

staff during this research program has already been used by NIST to provide its technical

advice to the JTC as well as other standardization committees.

1 .2 The Methodology

A methodology for accelerated aging of optical media is needed to estimate

media/systems life expectancy values. This methodology includes determining one or more media characteristics that define the end of life (EOL) for the media; a means of

accelerating the aging of the media; and a means of measuring the selected parameters.

Industry standards are needed to provide a commonly agreed upon basis for life expectancy testing so that vendor claims can be properly assessed by prospective users. These standards should include standard test methods for the selected media

characteristics and a standard methodology for estimating life expectancy values.

The initial expectation was that the methodology would be substrate independent.

Experiments were originally planned concurrently using polycarbonate and glass substrate

media. Test procedures were implemented for several media characteristics, including the

byte error rate (BER), the carrier-to-noise ratio (CNR) and blank area reflectance. For the

preliminary tests of these media characteristics, two types of 300 mm Write Once Read

Many (WORM) media were used: a glass substrate media and a polycarbonate substrate

media. NIST worked with industry to obtain support and contributions for the program.

These contributions consisted of equipment (including media) and technical support.

The polycarbonate substrate media used for the experiments was a type of Sony 300 mm

WORM. This media was run in a Sony WDD-3000 drive and Sony WDC-2000-10A

controller. The other media, was the ATG Gigadisc 300 mm WORM, which uses a glass

substrate. This media was run using an ATG GC/GD 1001 drive/controller. Both

controllers were connected to the host computer using a Small Computer System Interface

(SCSI) interface [4].

2
We assumed that a media characteristic such as the bit or byte error rate would reflect

better than other characteristics a general (average) degradation of the media under the

planned stress conditions. Initial degradation tests were run and BER, CNR and blank area reflectance were measured. Data was gathered from these parameters before the

initial aging tests and during the rest of the program to monitor the behavior of these

characteristics. The time consuming nature of these measurements and aging tests soon

became apparent. For this reason and budget limitations, we decided to concentrate

efforts on only one media type. The media used for the tests was the media of particular

interest to NARA, the 300 mm WORM polycarbonate substrate media [5, 6].

A measurement always involves errors which are inherent to the measurement system and

they should be kept in mind when the results are compared. Ideally, media and drives

from different manufacturers are used to correlate the results and separate causes and

effects of errors. However, most of the 300 mm WORM media from different manufacturers

are not interchangeable.

We initially intended to use the raw bit error rate as the quality parameter instead of the

BER. Measuring the bit error rate for the particular type of media would have required

building dedicated electronics to condition and acquire the proper analog signals in the

read channel, since the particular polycarbonate media selected for the experiments uses

an 8 of 10 modulation scheme. The advantage of acquiring data through dedicated

electronics and high speed instrumentation is that it is possible to acquire the user data as well as the sync and address information as analog signals. This approach allows for

studies of the analog signal degradation in different areas of the sectors. However, the

disadvantage of this method is that it is necessary to develop software for each drive and,

in some instances, dedicated hardware, as well. Another disadvantage is that, in general,

the amount of data that it is necessary to acquire is large and the instrument's memory

should be able to store this data. Measurements of error rates using a signal generator

for writing signals on the disks were not considered adequate at that time. Dedicated

testers or controllers were considered, but were not used because of cost, the lack of

standard formats, and technology limitations. Therefore, we decided to use commercially

available drives and controllers to acquire the data.

The disadvantage of this approach is that, in general, only user data can be accessed.

This means that some sectors on both the inner and outer area outside the user data area can not be accessed and error data in other parts of the sector are not available. Another

limitation of this approach is that it requires the use of the BER rather than the bit error rate as the quality parameter, since the bit stream is not available from the SCSI bus. Because

of the problems cited with using raw bit error rate and the fact that the manufacturer's

recommendation was to use the BER as the quality parameter, the BER was selected for

the tests. A BER value of 5 x

10'^ for the end of life (EOL) was also adopted. This value

is a typical number used by the manufacturers at the time of the beginning of this program.

For the BER measurement, the disks used in the experiments were divided into three

areas: inner, middle and outer. Each area was divided into blocks with a length of 300

sectors. The same pattern was written on each sector of a block. The BER on each disk

3
was calculated for the three different areas and for three different patterns (a high

frequency, a sequential and a random pattern) for studying pattern and area sensitivity.

This data was stored in computer files. After the media was subjected to the stress

conditions, the data was periodically read back and compared with the pattern information

to generate error information. This error information was stored in files to be processed

later. Before running the BER tests on media that was being aged, BER tests were also run on a control group of disks. The purpose of using a control group of disks was to

monitor the calibration of the drives used in the experiments.

Data was gathered at the beginning of the tests from the two surfaces of every disk under

test. However, data from only one of the two surfaces was actually included in the

calculations. A replacement policy was implemented in the event that a surface would

suffer accidental damage and would have to be replaced. The replacement policy was

that, if the surface used showed abnormal results because of an accident, the other

surface would be used thereafter. It was assumed that the two surfaces would have been

subjected to the same accelerating aging.

All the statistics used on the data assumed that if a byte is in error, the probability that the

next consecutive byte is in error is very small. This initial assumption implies that the errors were expected to be independent. Linear burst errors in the media are not accommodated

- under that assumption. Therefore, if a media testing plan expects that the number of burst

errors be high it would be necessary to design different mathematical tools to deal with

them. The same is true for defects that are several tracks wide. For effects that may

define the end of life prior to a general degradation of the media, methods other than

defining the EOL as a value of BER should be applied. For example, the EOL can be

defined as the time when the first uncorrectable read error occurs [7].

According to the statistical analysis done on initial BER data on a set of disks, the minimum

amount of data that has to be tested per surface and per area to obtain a BER value within

the range of ±0.074 times the BER observed with 90% confidence limits is approximately

23 MBytes (in this case a point estimator of 76x300x1024). (This assumes an initial BER

of at least .000021 ; smaller BERs not being significant.) If three areas are measured per

surface, this represents approximately 70 MBytes of tested data per surface. The amount

of bytes needed depends only on the estimated initial BER values and not on the total

capacity of the disk. That is, for a 1 GByte surface, the tested bytes would only be 7% of

the total capacity, while for a 3 1/2 80 MByte disks it would mean testing 87.5% of the total

surface.

Normal operating or storage conditions do not effect the media characteristics in a short

period of time. Therefore, tests of these parameters in a normal operational environment

are not useful to predict the media life expectancy. Thus, it is necessary to accelerate the

degradation in some way and apply a valid prediction theory. The Arrhenius model is frequently used with various kinds of materials for explaining aging effects at different

temperatures [8, 9, 10, 11, 12, 13]. It is easy to use and requires a smaller number of

stress conditions than other models. It can be used for optical media when the response

of the quality parameter to the stress conditions is fairly linear and a plot of extrapolated

EOL values (in hours) of the quality parameter versus an inverse value of the absolute

4
temperature T also has a linear response. This assumption implies that the defect increase

or the BER growth would respond to a first order rate equation, with the rate determined

by a single activation energy. The Arrhenius model was assumed to be suitable for the

media used in the experiments. It is desirable to use more stress conditions than the

minimum required by the model used. But, because of time constraints and cost

limitations, only three environments were chosen for the tests. Incorporating a fourth

environment would have reduced the extrapolation error. Other models require more

stress levels [9], [14]. For example, for the Erying model, the number of required stress

conditions is higher than for the Arrhenius model.

Laboratory testing always involves some measurement error. Therefore, results obtained

by applying this methodology may produce some deviations from a straight line. In addition, the degradation of a quality parameter such as the BER, which is a complex

function of several physical phenomena, will not necessarily respond only to a first order

rate equation. How much deviation from the straight line should be allowed and how good

the approximation of using relative humidity levels other than those of normal use

conditions is a task for the related standards committees.

The aforementioned assumptions are an approximation because it is not completely

adequate to infer before testing that the degradation mechanism would precisely fit the

Arrhenius model. Since the results are an approximation, it is also advisable to provide a way of deriving conservative life expectancy values.

Aging tests were run on selected sets of optical disks. The disks were supported vertically

in holders and put into the stress environments. The three environments created to age

the media were: 80 °C, 90% relative humidity (RH); 70 "C, 90% RH; and 60 "C, 90% RH.

To achieve the proper levels of stress, the temperature and RH were ramped-up at a

certain maximum rate after the media was placed in the chambers. Before removing media

from the chamber, the temperature and relative humidity were also ramped-down at a

certain maximum rate. The ramp-up and down conditions followed the manufacturer's

recommendation for the type of media tested. More conservative rate values (smaller

rates) can be used. Experiments were initially run on single pieces of media without

following these slopes. In one experiment, an oven was properly ramped-up and a short

aging cycle run in a single piece of media. But, before the media was removed from the

oven, the oven was shut off to simulate a loss of electrical power. Tests run for BER on

this sample showed an increase of BER that reached the EOL value of the parameter. This

experiment showed that care should be used in running these type of experiments.

The media was removed from its protective cartridge before subjecting it to the stress

conditions. The removal of the media from the cartridge introduces some handling

problems because the media is exposed to dust, fingerprints, and the possibility of

scratches. These problems can show up as systematic errors in the measurements.

While a single damaged disk may be merely removed from the test, damage to several

disks could jeopardize the significance of the data for the particular temperature and

relative humidity. Only one disk was damaged during the NIST testing. (The data

gathered from that surface was replaced in the calculations by the data gathered from the

other surface of the same disk). Users ordinarily have no need to remove media from the

5
cartridge and should not do so. If the risk of sudden abnormal behavior is high, it is advisable to incorporate more disks in the tests than the minimum required for the tests,

gathering data from all of them. The drawback to this is that time increases, meaning that

the disks will be out of the testing environment for a longer period of time. This may cause

some error in the testing.

BER values were derived from the three set of disks aged at the three high temperature

and humidity stress conditions. The median values were used instead of the mean as a more representative behavior of the three disks. The measured EOL values were

produced with three disks per set. Using more disks would have produced more precise

results, but would have cost considerably more. Plots of the quality parameter (BER)

versus the aging time were generated for each set of disks. These plots have generally

shown a straight line response. Modified Arrhenius plots were used with the data derived

from BER tests to demonstrate how to extrapolate life expectancy values. These modified

Arrhenius plots represent extrapolated life time values of the BER (in hours) versus an

inverse value of the absolute temperature (T). Extrapolated life expectancy values for room

temperature and the same relative humidity used for the stress environments were then

estimated from these modified Arrhenius plots for each of the patterns and areas used for

the BER measurements.

Other methods of life time predictions have been researched by NIST staff. For example,

[7] describes a method based also on the bit/byte error rate (or block error rate) as the

degradation parameter and in the determination of a kinetic model such as Arrhenius.

However, the end of life under the accelerated aging conditions is defined as the

occurrence of the first unrecoverable read error. Another method, included in the work of

the NIST/NASA working group for the development of test methods for ruggedized

rewritable media, includes a method which measures error rate derived from a signal

previously written with an external generator. In this method, the assumptions are similar

to the one used in the method used on this program [3]. There are instances where

localized defect growth could conceivably cause an uncorrectable read error prior to the

EOL value of BER. In those instances, prediction methods based on localized errors or uncorrectable read errors may be required. This is a subject of continued study in the

relevant standards committees. The occurrence of such uncorrectable read errors depends heavily on the error correction strategy used. This varies considerably between

manufacturers.

6
Chapter 2

Experimental Procedures

2.1 Introduction

An optical disk life expectancy methodology includes the selection of a set of media

characteristics that represent the degradation behaviour of the media, a plan for

accelerated aging tests, and the analysis, if possible, of failure mechanisms. Once the set

of media degradation parameters is selected, the next step is to identify which of these

parameters is critical for the definition of end of life of the media (EOL). This parameter is called the quality parameter. The approach used in accelerated aging is to measure the

change of the quality parameter under stress conditions to predict its behavior in normal

environments.

Media characteristics will not change significantly in a short period of time at normal

operating conditions. Therefore, tests of these parameters in a normal operational

environment are not useful to predict the media life expectancy. It is necessary to

accelerate the degradation in some way and apply a valid prediction theory. That means

being able to model the degradation of media characteristics at accelerated conditions

using the end of life parameter.

As it was explained in Chapter 1 , the Byte Error Rate (BER) was selected as the quality

parameter. The frequency spectrum of the read signal was also tested to derive carrier-tonoise (CNR) values. In addition, the reflectance of the blank areas was also measured.

These blank areas are located in the innermost and the outermost areas of the disks.

The optical disk drives were connected to the host computers using a SCSI interface as shown in figure 2.1 . The software for the drives to communicate with the host computers

was developed at NIST. This software is a SCSI command system that provides variable

structures and a library of SCSI commands for software assisted device control. A NIST

report describing the SCSI command system was published [4]. The following sections

describe the test methods implemented for the selected media characteristcs.

7
SCSI

I nte rf ac0

1 1- 0

1

SCSI Bus

Drive 1 Drive 2

Figure 2.1. System interconnection.

2.2 BER Measurements

2.2.1 Introduction

BER is defined as the ratio of the number of bytes in error to the total number of tested

bytes. Two approaches have been used to analyze the BER.

a.- BER Measured Over Three Areas on Each Surface

The first approach calculates BER using all three areas of the disk (inner, middle, and

outer) without differentiation of the area, and using only one pattern at the time. This

approach is being used by some manufacturers to report similar results. Three patterns

were used in different calculations (high density, random, and sequential pattern).

b.- BER Measured Using a Statistical Analysis on Three Independent Areas

The second approach uses a statistical analysis by area on the disk (inner, middle, and

outer) [15, 16, 17, 18, 19]. The data derived using this approach provides deviation values

from the mean, using the "Student t" distribution with confidence limits of 90%. However,

for some of the data sets analyzed, the deviation is high and does not show a good

representation of the data in semi-log scale. The data was recalculated deriving

information on median, maximum and minimum values versus aging time.

8
2.2.2 Measurement Procedure

The recording format of the polycarbonate media used for the experiments mixes the user data and the error correcting code (ECC) data within each sector of the disk. The glass

substrate media has separate areas in each sector for the user data and for the ECC

data. This difference has an effect on how the BER may be calculated for the two types

of media.

The BER for the first media was calculated for the user data portion of the sector only,

since the mixing of the user data and the ECC data makes it unlikely that the two would

have different BERs. This situation does not apply to the glass media, because the BER

might change from one value at the beginning of the sector to another value at the end of

the sector. Therefore, ideally, for these type of media, it would be preferable to separately

measure BER for both the user data and the ECC data areas. In the particular type of

glass media used for the initial experiments, this would have necessitated a measurement

technique that would have slowed the data acquisition by a factor of 25 times. For this

reason, the BER was also measured for the user data only.

As was mentioned in Chapter 1 , after the initial experiments using both types of media,

experiments continued using only the polycarbonate substrate media. Different patterns

were written in three areas on the disk to test for BER pattern sensitivity. The data were

read into files. After the aging process started, the data were periodically read back with

the ECC disabled and compared with the pattern information to generate BER information.

This error information was stored in files for further processing. Table 2.2 lists the different

phases of the BER measurement approach.

The disks were divided into three areas: inner, center and outer. Each area was divided

into blocks of 300 sectors each (see fig. 2.2). The same pattern was written on each

sector of a block.

Before running the BER test on media that had been aged, tests were run on a control

group of disks. When the results were different from the values previously measured from

the same control group, drive calibration problems were suspected and the drive was sent

for calibration. This happened once during the experiments.

Table 2.2. BER measurement approach

Phase I Phase II Phase III Phase IV Phase V

Phase VI

Write data on a selected group of disks

Read the initial error data and identify a control group

Age selected group of disks at different stress conditions

Read error data after every aging period

Using a database management system, calculate BER

Print and plot results.

9
Figure 2.2. Grouping of sectors for the BER measurement.

2.2.3 Database Management

Since the volume of error information was high, a database management system and a

database were used to handle the data. After the data was acquired, the database was

updated and the data were selected in different arrangements in order to analyze the BER

values for different patterns or areas.

2.2.4 Initial Tests to Determine the Statistical Analysis

In order to determine the statistical analysis to be used, and to have more understanding

of the error distributions, tests were run using both types of media. Three different

patterns were written three times each on the three different selected areas on these disks.

This patterns were: the sequential pattern, a random pattern, and a high frequency pattern.

In the sequential pattern, the bytes are in sequence from OOH to FFH. This pattern is repeated 4 times in the 1 024 bytes of the sector. The random pattern is a succession of

bytes generated by a random number generator. The high frequency pattern that does

not have any significant meaning for the glass media but for the polycarbonate media with

its 8 of 10 modulation it is the highest frequency that can be written on the media using

the SCSI bus. BER values calculated from this test were used to estimate the mean of the

BER for further statistical calculations. A statistical approach was used to determine the

10
number of sectors to be written on the three different areas of the disk. The confidence

interval and the confidence level were also calculated (see fig. 2.3).

Population Dlelrlbuf Ion: Binomial

Ipiiiiiiiiiiiiiiiiiiiinninniiiii

Inimiiiiiiiiiiiiiiiiuiuiiiiuif

Sampling Distribution: Normal

pllllllllllllllllllll H

Central Limit Theorem

umnii

iiiiiiimtiTTn

^ Estimate of

Illllllllllllllll fl

rtlllllllllllllllHTTTTtim Number of Samples

*Jtiiiiii llllllllllllll

iiiimiiimliiittninn Sample Size

N

iiiiiiiiiiiiiiiiiTiniiiri

nmmmini) Confidence

nterval d

iiiiiiiiimiiiiiimiiiii^

BER = p + d pop

Figure 2.3. Statistical approach for the BER measurement.

2.2.5 Determination of the Number of Bytes to Be Used for the Test

Each area of the disk selected for the BER measurement (the inner, middle, and outer),

was divided into 10 sections, which were numbered from 1 to 10. The sections were

divided into 4 partition tests, numbered from 1 to 4. The partition tests are areas where

only one type of test was allowed. The partition test 1 was designated for BER

measurement, number 2 for Frequency Spectrum tests, and 3 and 4 were reserved for

other tests.

According to the statistical method used, the number of bytes used for the initial BER

measurement was 70 Mbytes per surface distributed in the three different areas. Hence,

the minimum amount of data measured per area was approximately 23 Mbytes. The

results were extracted from plots of BER versus aging time for the different conditions as

will be shown in the next chapter.

11
2.2.6 Control Group of Disks

The control group was a set of disks which was stored in a normal operating environment.

The control group was used to determine that the disk properties under the stress

environments were varying solely due to the aging environments and not to other causes

such as changes in the measurement systems (which included the drives). Before

selecting the control group of disks, a large set of disks was tested for BER and the mean

and standard deviation of the BER was determined. The BER values were normalized to

Z scores and plotted. From this test, a control group was selected.

2.3 Blank Area Reflectance Measurement

2.3.1 Introduction

The objective of this measurement is to quantify the change in reflectance of the two blank areas of the disks. There are two areas per disk: the inner area, close to the center of the

disk, and the outer area, close to the outer edge of the disk. For the set of disks

subjected to the stress environments, blank refelctance values were determined between

aging cycles. The control group was also measured periodically. The blank reflectance

values were obtained by focusing a 830 nm GaAIAs solid state laser beam on the

recording layer of the media and measuring the level of radiation reflected to a photodiode

quadrature detector.

2.3.2 Measurement Procedure

The block diagram of figure 2.4 shows the interconnection of the hardware components

used to measure the blank area reflectance. A laser power supply delivers an adjustable

current to the laser diode. Quadrature photodetectors in the laser head assembly measure

the light returning from the recording layer and proportional voltage signals are amplified

in a servo amplifier driver. A focus voltage is returned to the laser head assembly by the servo amplifier driver to maintain focus on the recording layer. The quadrature

photodetector outputs are summed by an external operational amplifier circuit and a chart

recorder is used to record this voltage which represents the reflectance values.

The experiments were run using the polycarbonate substrate media mentioned above. It has two blank areas: approximately 5.9 to 6.7 cm from the center (inner blank area) and

14.2 to 14.7 cm from the center (outer blank area). The media was placed on a hub

inserted into an micrometric movement stage. The hub fits snugly into the media spindle

hole providing a media centering mechanism. The stage and media can be moved axially,

rotationally, and radially with respect to the laser radiation axis using a triple stage

controller. Reflectance values were recorded while rotating the media 360 degrees. The

system was calibrated using a semiconductor wafer. Ten values were taken for each

revolution and the mean, standard deviation and dispersion were calculated for each disk

of each set. Blank reflectance values were plotted versus aging time for the three sets of

disks.

12
These plots include the median values, the minimum, and the maximum for each set (see

chapter 3).

Laser Diode

Power Supply

Autofocua

Servo

Controller

Laser Head

Stags

Stage Motor

Optical Media

Quadrature

Photodlode

Amplifier

Stage Movement

Motor Controller

Strip Chart

Recorder

Figure 2.4. Reflectance measurement setup.

2.4 Carrier-to-Noise Ratio Measurement

2.4.1 Introduction

The measurement of the frequency spectrum allows derivation of characteristics such as

the carrier-to-noise ratio (CNR). Initially CNR was measured for both types of optical media

used for the experiments. As explained before, the experiments continued using only the

polycarbonate based media.

2.4.2 Recording a Carrier on the Media

In the glass media used for the experiments, data can be written on the media in a pattern

that produces a single frequency carrier. This carrier, when read back, is used to measure

the CNR.

13
SCSI

Interlace

SCSI Bua

Disk Drive 1 and Controller

Figure 2.5. Generating a carrier on the

media for disk drive 1

In this media, user data is segmented into 85 bit pieces separated by 15 bits of sync

information. Because the duration of a sync mark is an odd number of bits, the

complement of the bit pattern must be used in alternate blocks of data to maintain

constant carrier phase throughout the media. If this is not done, the fundamental is split

into two parts by the phase modulation. The carrier frequency for the media is chosen to

correspond to a repetitive "01" pattern. This is the highest frequency for which the

particular media is designed, and is considered worst case from an information density

standpoint. The pattern is written to the media using the diagnostic write SCSI command,

and a coherent 2.5 MHz carrier results (see fig. 2.5 for drive 1 , the drive that runs the glass

media).

As explained before, the polycarbonate media controller, on the other hand, uses an 8 of

1 0 bit modulation of data and the resulting sequence of bits written to the media contains

no alternating "01" patterns. As shown in figure 2.6, an external signal generator set to

2.6 MHz was used to drive the laser write circuit. To derive the CNR values, a SCSI write

command for the desired amount of written sectors was used. The drive was allowed to

control the address, blank area, tracking, servos and focusing, as it normally does.

14
SCSI

Interface

SCSI Bus

Signal Generator

Dlik Drive 1 and Controller DItk Drive 2 and Controller

Monotone

Signal

Write

Circuit

Figure 2.6. Generating a carrier on the media for disk drive 2.

2.4.3 Reading From the Media

A Hewlett-Packard 3585A spectrum analyzer was used to measure the frequency

spectrum to derive the CNR values. The test track was read and the signal level measured

using the spectrum analyzer with a center frequency equal to the maximum specified

frequency f^. The noise level was estimated by interpolating the average noise floor (see

fig. 2.7). The spectrum analyzer correction factor (2.5 dB) was substracted from the

difference between the signal level and the noise level. A program that acquires the data

from the instrument and calculates the CNR values was developed. This program also

plots the frequency spectrum of the read analog signal for a particular track. To position

the head on the proper track to measure the analog read signal from the glass media, the

"find first blank" SCSI command was used. This command tracks the media until a blank

sector is found or the controller searches the requested number of sectors. Figure 2.8

shows the measurement setup for this media type.

15
Figure 2.7. Amplitude versus frequency.

Dlik Drl»« 1 and Conlioller

Analog Read Signal Buffer AmplifierFigure 2.8. CNR measurement setup for disk drive 1

.

For the polycarbonate media, the controller continuously tracks both the address and the user data when a SCSI command is issued. Therefore, only one written track was

necessary to provide a signal for analysis (see fig. 2.9 for the measurement setup).

16
Spectruin Analyzer

Drift

Coatroilar Disk Dflft t

Analog Read

Signal

Figure 2.9 CNR measurement setup for disk drive 2.

2.5 Accelerated Aging Tests

As mentioned in Chapter 1 , aging tests were run on three sets of optical disks. Each set

consisted of three disks selected at random. Two ways were used to create the stress

environmens (80 "C, 90% RH; 70 °C, 90% RH; and 60 °C, 90% RH). For the 80 °C, 90%

RH enviroment, a temperature/humidity chamber was used. The T/H chamber is a

temperature/humidity cabinet that includes a microprocessor-based controller. The other

two stress environments were created using convection ovens containing desiccators in which saturated salt solutions were used to maintain constant relative humidity. Barium

chloride was used to control the relative humidity [20]. The manual oven controllers were

modified so that several ovens were controlled with a microcomputer through a multi-oven

controller designed at NIST (see fig. 2.10).

17
Ambient RHi Aprox. 40%

Humidity Seneor \

Thermocouple

Oven ExheuBt

Teit Environment

Disks Under Test

3

Saturated Salt Bath

Oven Temperature Control

D/A AID AID

Interface

Figure 2.10. Multi-oven controller.

The media was cycled up and down according to temperature and RH gradients that did

not exceed the manufacturer's recommendations. The set of disks were maintained at high temperature and relative humidity for periods of time. At the begining of the tests, the

aging cycles were 140 hours. The aging cycles were later increased to 500 hours between

tests.

Uninterruptible power supplies for the T/H chamber and the ovens were not available.

However, tests have been run to account for unexpected interruption of power because

of storms or other reasons. During a short interruption of power, the T/H chamber's

microprocessor-based controller holds the cycle and continues with the programmed cycle

after the power is restored. The multi-oven controller was designed so that upon an

interruption of power on the computer and the oven, the computer reboots with a program

that reads a file with information on which time and T/H have been recorded. The program

regains operation at exactly the same point as before the power interruption.

2.6 Visual Inspection of the Media and Defects Localization

Visual inspection of media which exhibits localized abnormalities such as high BER or high

reflectance aids in determining failure mechanisms. An optical bench equipped with a microscope, television camera, monitor and a hardware link to an image processing and

storage system was used to explore defects in the optical path and at the recording layer.

The measurement setup uses a polar coordinate system to return at a later time to an area

18
on the media where a defect was found. This feature allows the tracking of defects after

further aging. Figure 2.11 shows this optical image inspection system.

Image

Piocessing

TV

Monitor

TV Camora,

MIcrotoopa,

and

Optical Head

Servo Syalem

Pulee Driver

Oscilloscope

Laser Power

Supply

Optical DIak

X-Y-Z-R Stage

I

Host Computer

Figure 2.11. Optical inspection system setup.

19

Chapter 3

Results

3.1 Introduction

The results presented in this chapter were derived from the polycarbonate substrate media

used for the experiments (see Chapter 1). The following data shows results of BER

measurements and life time expectancy values derived from the three sets of disks that

were aged at three different high temperature and humidity stress environments.

Table 3.1 summarizes the stress conditions for these sets of disks. The table also shows

the total number of hours each disk set was aged. Data gathered on the sets that were

aged were analyzed at periodic intervals. In addition, data was also gathered from the set

of five disks that were used as the control group.

Table 3.1 Stress environments of high temperature and humidity.

Set # Disks Stress Environment Total Aging Time

1 15,22,24 60°C, 90%RH 5711 hr

2 26,27,28 70 °C, 90% RH 4120 hr

3 8, 14, 23 80 °C, 90% RH 4201 hr

3.2 BER Results

Figures 3.1 through 3.27 show the BER values versus aging time for the three stress

conditions shown in table 3.1. Three similar sets of charts follow. These sets show BER

values versus aging time in hours. The charts represent BER values calculated under

different conditions (using different areas and patterns). The charts show median,

maximum and minimum values of BER for sets of three disks where the data was read on

only one surface (side) of each disk. The dashed line on each chart is the linear

regression of the median values. The solid lines are the upper and lower 95% confidence

limits of the median. The charts also show a horizontal dash line that reflects the end of

21
life definition used to extract the EOL values (in hours). These EOL values are later used

in modified Arrhenius plots.

Each set of BER charts are divided in three subsets for each of the stress conditions:

60 °C, 90% RH; 70 °C, 90% RH; and 80 °C, 90% RH.

(a) Four graphs showing the aging effect on the BER values over all three areas written

on the disk using three different patterns (sequential, random, and high frequency).

The fourth chart of this subset is a comparative graph that includes the three

previous ones. This graph allows the reader to compare BER values extracted from

blocks of sectors written with different patterns. Note that BER values derived from

blocks written with the sequential or the random pattern show similar degradation

tendencies. On the other hand, the slope is higher on the plots derived from

reading blocks written with the high frequency pattern. This happens for the three

stress conditions. However, the difference is more noticeable for the 60 ° C, 90%

RH and 70 °C, 90% RH environments.

(b) Four graphs showing the aging effect on the BER values for all three patterns using

three different areas of the disk: the inner, middle, and outer area. The fourth chart

of this subset is a comparative graph that includes the three previous ones. This

graph allows the reader to compare BER values extracted from blocks of sectors

written with all the different patterns, but in three independent areas of the disks, as

explained before. The slopes are all similar for the 80 ° C stress condition. For the

other two stress conditions, the slopes on the inner and middle areas are similar,

but the slope is higher in the case of the outer area. Therefore, as the graphs

show, this outer area gives the smaller number of hours of extrapolated EOL.

(c) One graph showing the aging effect on the BER values on blocks of sectors in the

middle area, written with the high frequency pattern only.

Sets 1 to 3 - Stress Conditions: 60 " C, 90% RH; 70 " C, 90% RH; and 80 " C, 90% RH.

Figures 3.1 to 3.4, figures 3.10 to 3.13, and figures 3.19 to 3.22 show the aging effect on

the BER values over three areas of the disk using three different patterns. Figures 3.5 to

3.8, figures 3.14 to 3.17, and figures 3.23 to 3.26 show the aging effect on the BER values

for all the three patterns on three independent areas, the inner, middle, and outer. In each

of these areas, blocks of sectors have been written using three different patterns, the

sequential (00 to FF Hexadecimal), a pseudo-random pattern, and a high frequency

pattern, which is the hexadecimal value that produces the maximum linear density possible

for the type of disks used in the experiments. Figures 3.9, 3.18, and 3.27 show the aging

effect on BER on the middle area, selecting the blocks of sectors written only with the high

density pattern. The choice of this combination of area/pattern becomes apparent later.

Table 3.2 summarizes the EOL values (in hours) for the different sets under the three

different stress conditions. These values were extracted from the figures shown on the

following pages.

22
Note that in some cases, the figures do not show the intersection of the regression line

and the lower confidence limit with the BER end of life definition. The horizontal scale of

the figures could have been expanded to show these intersections, but it would have been

difficult for the reader to see the separate data points. Also, having the same scale for all figures makes visual comparisons easier.

23
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24
3.3 Application of the Arrhenius Model to the Data

3.3.1 Practical Considerations in the Application of the Arrhenius Model

The method of applying aging tests to optical disk media is relatively simple:

a) Stress environments are selected and the stress tests implemented. These tests

include decisions, such as for how long the set of disks will be aged and which is the

maximum temperature gradient to apply at the beginning and end of the stress cycles.

b) The quality parameter is selected or determined. Assuming that the quality parameter

is the byte error rate (BER), a measurement of BER and a data analysis method are

selected. Areas where the data is going to be written on the disks and which patterns to

be used are also selected.

c) Data on the BER values versus aging time are maintained for each of the different

environments selected. The slopes of these curves are then plotted versus an inverse

function of the absolute temperature. An alternative to these Arrhenius plots is to plot

extrapolated EOL values (in hours) derived from the BER plots versus an inverse function

of the absolute temperature. (The latter is the approach used in this investigation). In either case, the life expectancy value is determined by extrapolation.

To use the Arrhenius model, the first requirement is that the plot of the quality parameter

(BER) versus aging times should be a straight line. Deviations from a straight line reduce

the accuracy of the predictions. In the case of major deviations from a straight line, the

Arrhenius model may be not applicable for that parameter.

There are several important considerations to make in applying the Arrhenius model:

a) With limitations in testing time, some of the data on some of the disks do not reach

the BER value defined as end of life within a reasonable time. Therefore, extrapolations are needed. This results in an approximation of the true EOL values for that data.

b) Data for the Arrhenius plots should be determined for three or more points to ensure

that the EOL values actually do define a straight line.

c) If possible, the same drive should be used for all of the measurements with a given

set of disks so that drive calibration does not become a factor in the accuracy of the

results. If a drive must be replaced or calibrated during the testing of a set of disks, some

means must be used to correct the data values. The approach used by NIST to correct

data points generated with different drives, is described in a NIST publication [21].

25
3.3.2. Extrapolated Results From Modified Arrhenius Plots

Seven modified Arrlienius plots have been derived from tine extrapolated EOL values

shown on table 3.2 (see figs. 3.28 to 3.36). These plots use data points that are extrapolated end of life values (in hours) derived from the BER plots measured in three

different areas, and using three different patterns as shown in each particular figure. The

three points define a straigth line that is extrapolated to define the life expectancy values

at ambient temperature. The charts also include error bars derived from the upper and

lower 95% confidence limits of the BER median. Figures 3.28 to 3.30 show modified

Arrhenius plots for the BER from data for all three areas, using only one pattern at the time.

Figure 3.31 is a comparative graph which includes the three previous ones. Figures 3.32

to 3.34 show modified Arrhenius plots for the BER from data written in blocks of sector on

three independent areas, for all three patterns. Figure 3.35 is a comparative graph which

includes the three previous ones. Finally, Figure 3.36 shows a modified Arrhenius plot for

the BER from data written using only the high frequency pattern in the middle area of the

disk.

Table 3.3 summarizes the extrapolated life expectancy values (in years) derived from the

modified Arrhenius plots on figures 3.28 to 3.30. These extrapolations were done at room

temperature and at the same relative humidity used for the stress environments. The table

shows that the extrapolated life expectancy values are similar using the sequential pattern or the random pattern. However, the areas written with the high frequency pattern show

a shorter extrapolated life expectancy value. Note, as explained before, that the high

frequency pattern used on these blocks of sectors is the hexadecimal value that produces

the highest linear density possible in the disks used for the experiments.

Table 3.3 Extrapolated life expectancy values (in years) derived over

the inner, middle, and outer areas using three different patterns.

Sequential Random High Frequency

51 45 24

Table 3.4 summarizes the extrapolated life expectancy values (in years) derived from the

modified Arrhenius plots on figures 3.32, 3.33, and 3.34. These extrapolations were also

done at room temperature and at the same relative humidity used for the stress

environments. Note the dispersion in extrapolated life expectancy values derived from

measurements of BER in different areas of the disk surface. Visual inspection of the disks

showed damage effects produced by the stress conditions mainly in the outer areas, which

explains the difference in BER values in the outer areas with respect to the inner and

middle areas (see table 3.2).

26
Table 3.4 Extrapolated life expectancy values (in years) derived on

three independent areas using three different patterns

(high frequency, random, and sequential).

Inner area Middle area Outer area

140 242 12 (see text)

The Arrhenius model cannot accommodate secondary effects such as localized damages

on the disks. These secondary effects are due to causes such as some damage of the

sealing on the outer and inner edges of the disk due to the stress conditions that may

have allowed moisture to seep in, and the handling of the disks. While these temperatures

are normally used by some manufacturers, they may have been an excessive stress.

The difference between the BER values between the inner and outer areas may be

explained by the amount of damage, the difference in the linear distance, and possible

degradation of some of the mechanical characteristics in the outer area of the disks. A

contributor to the difference in extrapolated life expectancy values between the inner and

the outer areas may be the fact that in order to introduce the disks in the different stress

environments, they were positioned in a small holder and separated by teflon washers from

the center of the disks, which indirectly protected the inner area from secondary

degradation effects. Note that the extrapolated life expectancy values on table 3.3 are

also affected by these secondary effects. In this case these values reflect an average

behavior that also include the damaged areas.

For the reasons just cited, the outer and inner areas are excluded in Figure 3.36, which

shows a modified Arrhenius plot used to derive the extrapolated life expectancy value from

BER data measured only in the middle area and on blocks of sector written only with the

high frequency pattern (which gave the smaller life expectancy value in average of the

three areas). Figure 3.37 shows a more conservative extrapolation. The figure shows the

same modified Arrhenius plot of figure 3.36, but using an extrapolation of the upper 95%

confidence limit of the BER. In both cases extrapolated life expectancy values are derived

for room temperature and the same relative humidity used for the stress environments.

Table 3.5 shows the extrapolated EOL values of the BER over the middle area. Table 3.6

shows the extrapolated life expectancy values for this particular combination of

area/pattern.

Table 3.5 Extrapolated EOL values (in hours) over the middle area

60°C. 90%RH 70''C, 90%RH 80 "C. 90% RH

+95% 11,300 5.200 1,890

Median 15,200 8,000 1,970

-95% 24,750 34,300 2,050

27
Table 3.6 Extrapolated life expectancy values (in years) derived

over the middle area using the high frequency pattern.

Extrapolation of the

median values

Extrapolation of the upper 95%

confidence limit of the BER

121 57

3.3.3 BER Control Charts for the Control Group

Figure 3.38 shows a control chart derived from BER values for the control group. These

data are useful for supervising the measurement system, especially the drive behavior

along the duration of the program. This was explained in Chapter 2. Periodic BER

measurements of these disks show no degradation of this parameter, implying that the

measurement was under statistical control. Note that the hours plotted range from 3000

hours from the beginning of the experiments to 10000 hours. These data were taken

running BER measurements in the drive used for the experiments.

Before the tests shown in this figure, another drive was used for the experiments and

these type of data were also taken. However, this drive went out of calibration because

of the intensive tests run. This was detected using a control chart similar to the one

shown in figure 3.38. After the first 2000 hours of tests, the data for the control group run

in that drive went beyond Z = 3. These data were removed from the calculations of BER

derived from that drive. After the drive was sent for recalibration, tests of BER for the

control group showed again values of Z < 3. This approach is recommended to monitor

the behavior of the measurement system when monitoring of absolute parameters is cumbersome, time consuming, or the resources for recalibrating the measuring system

in-house are not available, as in this case. The assumption is that the control group of

disks does not change characteristics rapidly (especially the BER values).

3.4. Optical Inspection of the Media

As mentioned in Chapter 2, an optical inspection system has been used to visually

inspect the media between aging tests. The disks were periodically inspected between

aging tests. Some defects were located and the images stored. The typical defect size

was approximately equivalent to the width of four tracks, that is, a maximum value of 6.4

micrometers. Observations of the disks have also shown some spots, especially in the

outer areas of both the blank and user data areas. It is reasonable to infer that water has

penetrated the media through the outer seal. This effect was more severe for disks aged

at 80 ° C. From the results of BER, it is reasonable to infer that these spots are one of

the reasons why the BER in the outer areas was usually higher than in the other two.

These spots show in the results as systematic errors in the BER and EOL values.

28
3.5 CNR Results

Figures 3.39, 3.40, and 3.41 show the aging effect on the CNR values for three different

tracks, located in the inner, middle, and outer areas. The response was fairly flat for both

the disks aged at 60 °C, 90% RH and 70 °C, 90% RH. A decrease of CNR values can

be observed for the set of disks aged at 80 °C and 90% RH. The plots in figure 3.41

show that the decrease is more significant in the outer area than in the inner area. The

figure shows a worst case decrease of 10% of the CNR values on the outer track tested.

Figure 3.42 shows CNR versus time (in hours) for the control group. The plots show that

the response was fairly flat, denoting that variation of the CNR values in aged disks was

due to the stress environments and not because of measurement errors. The flat response of the control group shows no variation in the measurement conditions.

3.6 Reflectance Measurement Results

Figures 3.43 through 3.48 show reflectance of the blank inner and outer bands of each

surface for over 4000 hours of aging for the sets aged at 70 °C, 90% RH, and 80 °C,

90% RH, and for over 5000 hours for the set aged at 60 °C, 90% RH. The reflectance

measurement method used allows testing only the approximate area tested before.

However, the data collected is considered representative of the respective bands. The

maximum increase observed in the values is approximately 5% of the blank reflectance

values in both bands of the disks aged at 80 °C, 90% RH. Figures 3.49 and 3.50 show

reflectance values versus time (in hours) for the control group for the inner and outer

bands respectively. As in the case of the CNR experiments, the response for this group

was fairly flat, denoting that variation of the reflectance values in aged disks was due to

the stress environments and not because of measurements errors.

Il

29
30

32
t 7 1 2 2

aisy aojJ3 3)Xb

33
34
35
36
37
38
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56
Arrhenius Plot for the Byte Error Rate

(Inner, Middle, and Outer Areas)

I

1 1 1 \ : 1

10'

10^

D

O

10^ -

10^

Sequential Pattern

100 years

30 years

10 years

>.' I

5

70 X

60 *C

^1 - 80

J L J-^ _J L 2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5

1000/T [K ^] 25 X

Figure 3.28. Arrhenius plot for the BER (sequential pattern).

57
Arrhenius Plot for the Byte Error Rote

(Inner. Middle, and Outer Areas)

1

[Random Pattern |

10^ 100 years

30 years /

/

/

10^

'/

10 years

r. /

-

X./

'. / I 60 *C

. 1= 70 OQ

-

10^ -1

:

' 80

1

1 1 2.8 3.0 3.2 3.4

1000/T [K ^] 25 ^'C

Figure 3.29. Arrhenius plot for the BER (random pattern).

58
Arrhenius Plot for the Byte Error Rote

(Inner, Middle, and Outer Areas)

10'

1— 1 1—:—

r

High Frequency Pattern

10^

D

OX

10

10^

100 years

30 years

10 years

f t 60 *C

70 «C

- 80 *C

J I I I L

2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5

1000/T [K ^] 1_ 25 *C

Figure 3.30. Arrhenius plot for the BER (high frequency pattern).

59
Arrhenius Plot for the Byte Error Rate

(inner. Middle, ond Outer Areas)

1 I 1 1 (

1

jsequentiol Pottern

100 yeors

s t

50 Y*ort

/

-

'

10' 10 yeors

10*

/ 1 60 "C •' \—70'c

10'

' ^ 80 *C

1 1 1

i 1

1 2.6 2.9 3.0 3.1 3.2 3.3 3.4 3.5

1000/T [K"'] t 25 -C

(a)

Arrhenius Plot for the Byte Error Rote

(Inner. Middle, ond Outer Areos)

,8 _ 100 yeorB

30 yeora

Rondom Pottern

10 years

2.8 3.0 3.2 3.4

1000/T [k"']

(b)

Arrhenius Plot for the Byte Error Rate

(Inner. Middle, ond Outer Areos)

oX

t 1 t V r

|Hiqh Frequency Pottern

|

r

10^ 100 years

30 yeora

r

10* 10 years

^

10'

10'

\ 60 °C

1 70 X

:\

:

' so *c

1 1 1 1 1 1 2.8 2.9 3.0 3.1 3.2 3.3 3.* 3.5

1000/T [k"'] t 26 -C

(c)

Figure 3.31. Arrhenius plots for the BER (three patterns).

60
Arrhenius Plot for the Byte Error Rote

(High Frequency, Random, and Sequentiol Patterns)

I

1 1 1 1—

10^ 100 years

30 years

10^

if) \-

D

O

10

10^

Inner Area

10 years

r y t

70 ^'C

60 X

80 ^'C

J I I I I :

I 2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5

1000/T [K ^] L_ 25 °C

Figure 3.32. Arrhenius plot for the BER (inner area).

61
Arrhenius Plot for the Byte Error Rote

(High Frequency, Random, and Sequential Patterns)

10' 100 years

30 years

10^

(n

V-D

O

X

10

10^

1 : rr

[MiMiddle Area

10 years

A

t

70 *C

60

80 X

2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5

1000/T [K ^] 25 ''C

Figure 3.33. Arrhenius plot for the BER (middle area).

62
Arrhenius Plot for the Byte Error Rote

(High Frequency, Random, and Sequential Patterns)

1 i 1 1 1 Outer Area

100 years

30 years

10 years

Vf O

X

y

y

V \1 _ 60 *C

' 70 **C

> 80

1 1 1 1 1 : 1 2,8 2.9 3.0 3.1 3.2 3.3 3.4 3.5

1000/T [K ]

' 25

Figure 3.34. Arrhenius plot for the BER (outer area).

63
Arrhenius Plot for the Byte Error Rote

(High Frequency, Random, and Sequentioi Patterns)

1 1 1 1 r

1

10®- yeors

JO years

Inner Areo

10 years

,1

80 'C

_1 J I I I . l_ 2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5

1000/T [K~'] t 25 «C

(a)

Arrhenius Plot for the Byte Error Rote

(High Frequency, Rondom, ond Sequential Potterns)

10"

Middle Area I

100 yeor^

30 years

10 yeorsX

2.8 2.9 3.0 3.1 3 2 3.3 3.4 3.5

1000/T [k"'] ^ 85 °C

(b)

Arrhenius Plot for the Byte Error Rote

(High Frequency, Rondom, and Sequential Patterns)

1 1 1 [ 1

1 Outer Areo

|

I

10^ 100 years

30 yeora

1 0 years ^

'

01DOr

10*

, ^ t 60 "C

: ^ 80 "c

1 1 1 1 L 1 2 8 2.9 3.0 3.1 3.2 3.3 3.4 3.5

1000/T [k"'] 1 25 "C

(c)

Figure 3.35. Arrhenius plots for the BER (three areas).

64
Arrhenius Plot for the Byte Error Rate

Middle Area/High Frequency Pattern

1

100

1 1 1 1

years

/

/

: '

/

/

/

I /

r

/

/

/

/

30 years

10

/

/

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v)

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1

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1

I 60 *»C

10^

rT

1

70 *»C

80 *»c i

1 1 1 1 : 1 2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5

1000/T [K ^] 25

Figure 3.36. Arrhenius plot for the BER

(middle area/high frequency pattern).

65
Arrhenius Plot for the Byte Error Rote

Middle Area/High Frequency Pattern

10' 100 years

10^

(0

D

OX

10

10^

30 years

10 years

60 *C

ft

70 ^'C

80 *C

J I I L

2.8 2.9 3.0 3.1 3.2

1000/T [K~^]

3.3 3.4 3.5

1_ 25

Figure 3.37. Arrhenius plot for the BER

(middle area/high frequency pattern, upper 95% confidence limit).

66
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Aging Effect on Reflectance (Inner Blank Area)

30

25

20

15

10

5

--

—I

1 Disks: 15, 22, and 24

T

_L

Max. Values

Median Values

Min. Values

I 1000 2000 3000 4000 5000

Aging Time in Hours (60 °C, 90% RH)

Figure 3.43. Reflectance versus aging time (inner blank area).

6000

\ I oC

COo

i-H

Pi

30

25 --

20 --

15

10

5

--

Aging Effect on Reflectance (Outer Blank Area)

1 1 1 —

I

1 Disks: 15, 22, and 24

, 5 .a

'-4

r

V Max. Values

Median Values

Min. Values

1000 2000 3000 4000 5000

Aging Time in Hours (60 ^C, 90% RH)

6000

Figure 3.44. Reflectance versus aging time (outer blank area).

72
o

a

COo

O

C

(0o

«4-l

Aging Effect on Reflectance (Inner Blank Area)

30 -,

25

20

15

10 --

5

--

I I Disks: 26, 27, and 2Q

V

Max. Values

Median Values

Min. Values

1000 2000 3000 4000 5000 6000

Aging Time in Hours (70 °C, 90% RH)

Figure 3.45. Reflectance versus aging time (inner blank area).

Aging Effect on Reflectance (Outer Blank Area)

30

25 --

20

15

10 --

5 --

—I

1 Disks: 26, 27, and 28

T Max. Values

Median Values

Min. Values

I 1000 2000 3000 4000 5000 6000

Aging Time in Hours (70 ^C. 90% RH)

Figure 3.46. Reflectance versus aging time (outer blank area).

73
o

C

m

o

1—4

30

25

20

15 --:

10 --

5 --

Aging Effect on Reflectance (Inner Blank Area)

1

1 1 —1

1 Disks: 8. 14, and 23

. •

Max. Values

Median Values

Min. Values

1000 2000 3000 4000 5000

Aging Time in Hours (80 °C. 90% RH)

6000

Figure 3.47. Reflectance versus aging time (inner blank area).

Aging Effect on Reflectance (Outer Blank Area)

30

o

C

(0o

«*-<

25 --

20

15

10 --

5

--

1 I Disks: 8, 14, and 23

V Max. Values

Median Values

Min. Values

1000 2000 3000 4000 5000

Aging Time in Hours (80 °C. 90% RH)

6000

Figure 3.48. Reflectance versus aging time (outer blank area).

74
Reflectance Values for the Control Group (Inner Blank Area)

25

o

fio

<(-( 0)

20

15 3r

10 --

5

--

V Max. Values

H Median Values

Min. Values

2000 4000 6000

Time in Hours

8000 10000

Figure 3.49. Reflectance values for the control group

(inner blank area).

Reflectance Values for the Control Group (Outer Blank Area)

6^

V

V

tdo

ID

(L)

25 --

20

15

10 Max. Values

Median Values

Min. Values

2000 4000 6000

Time in Hours

8000 10000

Figure 3.50. Reflectance values for the control group

(outer blank area).

75

Chapter 4

Conclusions and Recommendations

4.1 Conclusions From the BER Results and the Extrapolations

From the Modified Arrhenius Plots

The methodology as applied to one type of 300 mm WORM disks produced the following

results:

a) When plotted on a semi-log chart versus aging time for the different environments,

the BER values shows a generally linear response. In a few instances, there were

some deviations from the straight line. How much deviation from the straight line

should be allowed is a task of the standards committees. Possible causes of these

deviations are due to experimental error, handling of the disks, degradation of some

mechanical characteristics during aging, and effects of the high temperature and

humidity stress conditions on the outer and inner seals which produced some

localized defects on the disks. While these stress conditions are used by

manufacturers for this type of media, in some cases they may have been an

excessive stress. Users should note that media will never be used at the stress

conditions used in these tests. Therefore, the secondary effects encountered during

the aging procedures would not normally occur. These stress conditions are well

beyond the storage or operating environment.

b) When BER values are calculated for three independent areas on each surface, the

extrapolated end of life (EOL) values of the BER (in hours) are different for each

area. The extrapolated EOL for the outer area gives the smallest (shortest time)

values (see table 3.2). These differences are in part the result of secondary effects

for which mathematical models such as the Arrhenius model do not apply. Section

3.3.2 discusses these secondary effects.

c) When BER values are calculated for three different patterns over the inner, middle,

and outer areas on each surface, the extrapolated EOL values of the BER (in hours)

are different for each pattern (see table 3.2). EOL values of BER derived using the

high frequency pattern produced a shorter EOL estimate than the use of the other

two patterns, which indicate no significant differences of extrapolated EOL values

of the BER.

77
Modified Arrhenius plots derived from tlie extrapolated EOL values for the BER

shown in table 3.2, indicate different extrapolated life expectancy values, depending

upon the method used to derive the BER values as indicated in items (b) and (c)

(see tables 3.3 and 3.4). For example, table 3.3 shows extrapolated life expectancy

values derived from blocks of sectors written with three different patterns. Those

values are: 51 years for the sequential pattern, 45 years for the random pattern, and

24 years for the high frequency pattern. The conclusion derived from the these

results, according to the values in table 3.3, is that using different patterns for the

experiments gives different results. The results show that different approaches for

measuring the quality parameter (in this case the BER) can cause different

extrapolated EOL values and consequently different extrapolated life expectancy

values. In this experiment, these values reflect an average behavior that include the

three areas mentioned above. Note that the extrapolated life expectancy values are

for room temperature and the same relative humidity used for the stress

environments.

Figure 3.36, shows a modified Arrhenius plot which represents the extrapolated life expectancy value from BER data measured only in the middle area (less susceptible

to secondary effects) and on blocks of sectors written only with the high frequency

pattern which gave the smaller life expectancy value (more conservative figure).

Table 3.5 shows the extrapolated EOL values (in hours) over the middle area. Table

3.6 shows that the extrapolated life expectancy value for this particular combination

of area/pattern is 121 years (for an extrapolation of the median values). Figure 3.37

shows a more conservative approach using the same set of data, but extrapolating

the upper 95% confidence limit of the BER values. Table 3.6 shows that the

extrapolated life expectancy value for this approach is 57 years. These extrapolated

life expectancy values are also for room temperature and the same relative humidity

used for the stress environments.

The results from the BER measurements are repeatable. While the measurement

system used has its limitations because the tests were run in commercially available

drives and there is no way to do an absolute calibration unless the drive is shipped

back to the manufacturer's facilities, the data was sufficiently stable as shown in the

figures. (Alternatives are very expensive; tests beds for BER and other media

measurements range approximately from $1 00,000 to $500,000.)

Using a commercially available disk drive means that the drive may have to be

recalibrated during the test period. This situation may be discovered by periodic

testing of the control group of disks. If this occurs, the quality parameter data for

that time period must be corrected or disregarded. This situation occurred on one

occasion during the experiment. However, when the drive was returned from

calibration by the manufacturer, data generated using that drive and the control

group of disks showed that the drive was again correctly calibrated.

78
h) The EOL values derived from the BER plots were produced with three disks per set. Using more disks would produce more precise results, but would add considerably

to the cost.

1) As pointed out above, a strict use of the Arrhenius model would require that plots

of the quality parameter (in this case the BER) versus the aging time to be a straight

line and plots of extrapolated EOL values (in hours) of the BER versus 1 000/T also

be a straight line.

j) The data shows that the extrapolated life expectancy values for the media strongly

depend of the testing conditions, the patterns used, the areas measured, etc.

k) CNR decreased 10% for the set aged at the maximum temperature and 90% RH.

However, the other two sets aged at smaller temperatures showed a fairly flat response. There were not sufficient changes in this parameter to be included in the

definition of EOL. CNR tests run in a control group showed a flat response in over 9000 hours of testing.

I) Reflectance values increased no more than 5% in the sets aged at the three

different stress environments. As in the case of CNR, there were not sufficient

changes in this parameter to be included in the definition of EOL. Reflectance tests run in a control group showed a flat response during the testing period.

4.2 Discussion and Recommendations

The most important conclusion of our work is that extrapolated life expectancy values mav

vary greatly because they depend, among other factors, on the test method used for

calculating the guality parameter (e.g.. BER). the measurement approach including data

patterns used, areas measured (e.g.. middle area), amount of data tested, mathematical

model used, criteria for data analysis (including the statistical analysis used, confidence

intervals, etc), and the stress conditions. Therefore, users should be aware that claims of a life expectancy specification should be accompanied by specification of the above

factors.

The results shown in Chapter 3 and in section 4.1 indicate that the methodology applied

to a small sample of disks yields a range of extrapolated life expectancy values depending

upon the patterns and areas used for the BER measurement. The range of extrapolated

life expectancy values derived using three different patterns includes data taken in areas

of the disks where secondary effects took place. These secondary effects cannot be

accomodated by the mathematical model used for the extrapolations.

We also used another approach to analyze the data. In this approach we selected the

data derived only from the middle area (assuming that these areas of the disks were the

more isolated from the secondary effects) and from sectors written only with the high

frequency pattern (worst case pattern for this implementation). Using these more

79
representative data (high frequency pattern in the middle area) and median values of the

BER, we derived an extrapolated life expectancy of 121 years at room temperature and

90% RH. Using for the extrapolations the upper 95% confidence limit of the BER, we

obtained a more conservative extrapolated life expectancy value of 57 years at room

temperature and 90% RH. However, assuming a typical RH range for a storage

environment of 40% to 50% RH, the projected life expectancy values using this method

should be longer than the ones derived from our experiments.

These results are an approximation and should be used with caution because the

experiments used a small number of samples and the presence of degradation effects

which do not correspond to the prediction model. Furthermore, it should be noted that

the higher than normal humidity levels used to permit aging disks in a reasonable length

of time influences the results.

Our results imply that different testing methods have the potential for deriving different

values of extrapolated life expectancy, all of which may be valid. The need for standard

test methods for life expectancy is apparent. Industry standards would provide a

commonly agreed upon basis for life expectancy testing so that vendor claims can be

properly assessed by prospective users. Otherwise, comparisons between different

products will not be possible.

The method employed in the NIST experiments used the Byte Error Rate (BER) as the

quality parameter. This method uses BER average values that give a general indication

of the behavior of the media. For effects that may define the end of life previous to a

general degradation of the media, other methods should be applied, such as defining the

EOL as the first uncorrectable read error.

The Arrhenius model is easy to use and the required stress conditions are less than for the

application of other models. For example, the number of stress conditions for the Erying

model is higher than for the Arrhenius model. The Arrhenius model can be utilized for

optical media when the response of the quality parameter to the stress conditions is fairly

linear and the extrapolated EOL of the quality parameter versus an inverse value of the

absolute temperature T also shows a linear response. How much deviation from the

straight line should be allowed and how good the approximation of using relative humidity

levels other than the use conditions is a task for the related standards committees. As

long as the general response is similar, it would be possible to apply the same

methodology to disks of other types.

Sets of disks were aged using high temperature and relative humidity as the stress

conditions. Plots of the quality parameter (BER) versus the aging time have shown in general a straight line response and modified Arrhenius plots were used to show how

extrapolated life expectancy values can be derived.

If the risk of sudden abnormal behavior is high, it is advisable to use more disks than the

minimum required for the tests, gathering data from all of them. The drawback to this

approach is that the disks will be out of the testing environment for a longer period of time.

This may cause some error in the testing.

80
General conclusions on the extrapolated life expectancy values of other types of media will require implementing the methodology described to those types of media. It may be that

the methodology might have to be adapted for some types of media (e.g., magneto-optic

media might need different aging conditions, EOL definition, and model that fits the data,

etc). Consequently, the methodology is applicable to other types of disks (perhaps with

some modifications as stated above), but the results may vary considerably. This program

provides the basis for such work. Candidate media include other types of WORM media

and rewritable media, and media with different types of substrate, such as polycarbonate

and glass. Tests run in different laboratories using the same general methodology should

derive similar results as long as the chosen stress conditions are the same and the other

testing conditions are followed.

There are instances where localized defect growth could conceivably cause an

uncorrectable read error prior to the EOL value of BER. In those instances, prediction

methods based on localized errors or uncorrectable read errors may be required. This is a subject of continued study in the relevant standards committees in which NIST is participating. The occasion of such uncorrectable read errors depends heavily on the error correction strategy used. This technique varies considerably between manufacturers.

During this program other methods of life time predictions have been studied by NIST. A

recent submission to the JTC on Data Permanence is based on the bit/byte error rate (or

block error rate) as the degradation parameter and in the determination of a kinetic model

such as Arrhenius. However, in this submission, the life expectancy at the accelerated

aging conditions is defined as the occurrence of the first unrecoverable read error.

4.3 Related Programs at NIST on Data Preservation

Currently NIST is involved in three programs related with issues of data preservation on

optical media. These programs are:

(a) A program to investigate the status of on-line monitoring techniques for error rates

and error distributions. Under this program a workshop was organized to identify

on-line monitoring techniques in current products and suggested methodologies for

on-line error rate monitoring. During the workshop a set of user requirements was

identified and an government/industry working group was organized. This working

group is sponsored by the Computer Systems Laboratory of NIST. The goals of

the working group are to build an industry consensus for a method(s) of reporting

error rate information through an interface as indicated by the results of the

workshop. Included in this program is the implementation of a test/demonstration

platform consisting of a workstation (s) and optical disk subsystem (s) that

incorporate provisions for error rate reporting. The program also allows for

participation in the relevant standards committees.

(b) A program sponsored by NASA to develop test methods and specifications for 356

mm ruggedized rewritable media. A working group with members of NIST, NASA

81
and industry was formed. A set of test methods were developed and they are included in NIST Special Publication 500-1 91 . The test methods document includes

recommendations to test the life expectancy of the media.

A care and handling study of optical media sponsored by NARA and NIST.

82
5. References

[1] Geller, S., The National Bureau of Standards Research Program for the Archival

Lifetime Analysis of Optical Digital Data Disks; SPIE Vol. 490, Applications of Optical

Digital Data Disk Storage Systems, 1 984.

[2] American National Standard, ANSI X3.199 - 1991, Test Methods for Media

Characteristics of 356 mm Optical Disk Cartridge - Write-Once.

[3] Podio, F., Test Methods for Optical Disk Media Characteristics (for 356 mm

Ruggedized Magneto-Optic Media), Natl. Inst. Stands. Technol. Spec. Publ.

500-191; September 1991.

[4] Gorczyca, J., Sanchez Villagan, E., Small Computer System Interface (SCSI)

Command System. Software Support for Control of Small Computer System

Interface Devices. Nat'l. Inst. Stands. Technol., NISTIR 89-4023; January 1989.

[5] Nakane Y., Sato N., Makino H., Miyaoka S., Principle of Laser Recording Mechanism

by Forming an Alloy in the Multilayer of Thin Metallic Films; SPIE Vol. 529, Optical

Mass Data Storage, 1985.

[6] Optical Storage Technology Group, Sony Corporation of America, Recording

Principle and Reliability Study of Sony Century Media, April 1988.

[7] Murray W., Life Expectancy of Optical Systems, submitted to Joint Technical

Commission ANSI IT9-5/AES, Task Group IV, Optical Systems; October 1990.

[8] Bard, C, Larson, G.W., Hammond, H., Packard, C, Predicting Long-Term Dark

Storage Dye Stability Characteristics of Color Photographic Products From ShortTerm Tests, Journal of Applied Photographic Engineering, Vol. 6 No. 2 April 1980,

pp. 42-45.

[9] Thomas, R. E., Gorton, H. C, Research Toward a Physics of Aging of Electronic

Component Parts, Symposium on the Physics of Failure in Electronics, Chicago, IL 1963.2- SPIEGEL.

83
10] Vinson, J. R.; editor, Advanced Composite Materials-Environmental Effects,

American Society for Testing and Materials, STP 658, 1977.

11] Takahashi, A., Katayama, H., Inui.T., Ohta.K, Yamaoka, H., High Quality MagnetoOptical Disk. SPIE Vol. 695, Optical Mass Data Storage II; August 1986.

12] Storey, P. A., Longman, R. J., Davies, N. A., Environmental Evaluation of Rugged

and Long-Llfe Write Once Optical Disks. SPIE Vol. 899 Optical Storage Technology

and Applications; January 1988.

13] Dyball, C, Service Life Estimation by Arrhenius Extrapolation, Mountain View, CA,

Drexler Technology Corporation, August 1987.

14] Milch, A., Tasaico, P., The Stability of Tellurium Films in Moist Air: A Model for

Atmospheric Corrosion, Journal of the Electromechanical Society, Vol. 127 No. 4,

April 1980, pp. 884-891.

^5] Spiegel, M. R.; Theory and Problems of Statistics, Shaum's Outline Series,

McGraw-Hill Book Company, 1961. 124

16] Johnson, R.; Elementary Statistics, 3rd edition, Duxbury,1980. 235.

17] Huntsberger, D. V.; Element of Statistical Inference, 2nd edition, Allyn and Bacon,

Inc., 1969. 129.

18] Johnson, R.; Elementary Statistics, 3rd edition, Duxbury,1980. 251.

19] Huntsberger, D. V.; Element of Statistical Inference, 2nd edition, Allyn and Bacon,

Inc., 1969. 129.

20] Humidity Fixed Points of Binary Saturated Aqueous Solutions, J. Res. Natl. aBur.

Stands. (U.S.), A. Physics and Chemistry Vol. 81 A, No. 1, January-February 1977.

;21 ] Natrella, M., Experimental Statistics, Natl. Bur. Stands. (U.S.) [now Nat'l. Inst. Stands.

Technol.]; Handb. 91, Chapter 5; August 1963.

84
NiST-1 14A U.S. DEPARTMENT OF COMMERCE

(REV. 3-90) NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY

BIBLIOGRAPHIC DATA SHEET

1. PUBUCATION OR REPORT NUMBER

NIST/SP-500/200

2. PERFORMING ORQANIZATION REPORT NUMBER

3. PUBUCATION DATE December 1991

4. TITLE AND SUBTITLE Development of a Testing Methodology to

Predict Optical Disk Life Expectancy Values

5. AUTHOR(S)

Fernando L. Podio

6. PERFORMINQ ORGANIZATION (IF JOINT OR OTHER THAN NIST, SEE INSTRUCTIONS)

U.S. DEPARTMENT OF COMMERCE

NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY

GAITHERSBURG, MO 20899 Computer Systems Laboratory/ Advanced Systems Division

7. CONTRACT/GRANT NUMBER

8. TYPE OF REPORT AND PERIOD COVERED

Final

SPONSORING ORGANIZATION NAME AND COMPLETE ADDRESS (S1 REET, CITY, STATE, ZIP) National Archives and Records

Administration

Washington, D.C. 20408

10. SUPPLEMENTARY NOTES

11. ABSTRACT (A 200-WORD OR LESS FACTUAL SUMMARY OF MOST SIGNIFICANT INFORMATION. IF DOCUMENT INCLUDES A SIGNIFICANT BIBUOGRAPHY OR

UTERATURE SURVEY, MENTION IT HERE.)

There are no standards for longevity of optical disks that can assist managers in the Federal

government to select the right media for the storage of permanent records, and to know how

long the information may be safely stored on those disks. This report focuses on research

undertaken at the National Institute of Standards and Technology to develop a methodology

to predict optical disk life expectancy values. In this research accelerated aging tests were run on small sets of disks and the quality parameter (the byte error rate) was periodically measured between aging cycles. These tests were used with a mathematical

prediction model to develop a testing methodology.

This report presents the results obtained. The need for standard test methods for predicting

life expectancy and for measuring media characteristics is apparent. Life expectancy

extrapolations derived from the experiments produced a range of values depending upon the

method used for deriving the quality parameter. Recommendations are made about the

implementation of a testing methodology for life expectancy predictions, and what information

to include in a life expectancy specification.

12. KEY WORDS (6 TO 12 ENTRIES; ALPHABETICAL ORDER; CAPITAUZE ONLY PROPER NAMES; AND SEPARATE KEY WORDS BY SEMICOLONS)

accelerated aging; Arrhenius model; byte error rate; media lifetime; optical disks, stress

tests;y optical — £- ^ disks, test — methods. — -

13. AVAILABIUTY 14. NUMBER OF PRINTED PAGES

96

X UNUMITED

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