Storage Reliability

John P. Rooney; Sippican, Inc.; Plymouth, MA

Key Words: Storage, Storage Reliability, Dormancy, Reliability Prediction, Sonobuoy

Missiles, mines, and sonobuoys are examples of devices which are required to survive prolonged periods of storage and to perform acceptably immedJately upon removal from storage. A missile, for example, may be stored in a silo for 5-10 years and then be required to operate upon the receipt of a firing command. With these expendable devices, storage reliability dominates the efforts in achieving the mission reliability goal.

Complex computer systems are sometimes assembled, de-bugged, and then placed into storage to await the completion of the physical plant.

In such cases, a nationally accepted source of storage failure rates has been needed to perform predictions forJhe effects of storage. The lack of such a source has forced some companies to run experiments, gather data, and develop an in­house list of storage failure rates.

In 1985, Rome Air Development Center, Rome, NY, published RADC-TR-85-91, Impact of Nonoperating Periods on Equipment Reliability [1], which provides a concise volume for the calculation of storage failure rates. RADC-TR-85-91 is designed to provide the nonoperati!1g reliabilio/ prediction equivalent of MIL-HDBK-217. ThIS paper reVIews the methods and models of RADC-TR-85-91. Example calculations are presented, and statistical techniques are used to compare the data from the literature with the RADC­calculated storage failure rates for simple components, systems, and an exotic component.

Areas for improvement are noted, including the refinement of the environmental factors, addition of methods to deal with surface mount components, and (for completeness) a section on nonelectronic components. Components with a known shelf life should be clearly identified, so that analysts do not attempt to predict a stora&elailure rate beyond the end of life for those components.

Introduction

The approach for dealing with storage reliability has been formalized for some time. Almost three decades ago, in his seminal textbook on reliability [2], Igor Bazovsky recognized that a comr.:nent has an operating failure rate and a "quiescent' failure rate. Bazovsky then furnished a reliability model, requiring:

{1� operational failure rate, 2 time spent in the operational mode, 3 "quiescent" or storage failure

rate, (4) time spent in the storage mode.

System reliability is then a summation of each failure rate type (operational or "quiescent") for each component in the system and an evaluation of the usual exponential reliability equation for the time spent in the respective mode (operational or "quiescent"). Sources for operational failure rates for electronic and mechanical components have also been available. For operational reliability of electronic parts, MIL­HDBK-217, Military Handbook. Reliability Prediction of Electronic Equipment {3] has been the source of predictive numerics. For mechamcal parts, NPRD-3, Nonelectronics Parts Reliabili� Data [4] has been the source. With the publication of ADC-TR-85-91, we have a volume which can become the nationally recognized source for storage failure rates.

RADC-TR-85-91

For years, reliability analysts have emphasized operational failure rates, particularly with electronic components. The gathering of data and the development of models for operational failure rates have produced the various revisions of MIL-HDBK-217 [3], which have been recognized as the national (and international, even in the face of some competition) standard for the calculation of operational failure rates for electronic components. The publication of RADC­TR-85-91 in May 1985 has provided a candidate for a nationally accepted source for storage failure rates.

Necessity forced many companies and Government organizations to perform independent studies to �et�rmine the effects of storage on parts and to produce a compilatIon of storage failure rates for electronic and nonelectronic components.(See [5],[6],[7],[81,[9]). These studies were required to resolve uncertainties in the mission reliability of devices which spend a considerable portion of their life in storage. This independent work formed the basis for RADC­TR-85-91, which was produced February 1983 to September 1984 (complete list of references is included in RADC-TR-85-91).

The nonoperating failure rate data were sorted by component class. Regression analysis and other statistical techniques were used by RADC analysts to develop a model for each component class. The individual component model is therefore based primarily on numerical analysis of the observed data. Each model was intentionally made similar to the MIL­HDBK-217 operational model.

Generally, each model has a base nonoperating storage failure rate, temperature factors, quality factors, and on-off cycling factors.

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178 1989 PROCEEDINGS Annual RWABIUTY AND MAINTAINABIUTY Symposium

Dorman!;,Y

Dormancy has been defined as equipment states in which equpment is in its normal operation configuration and is connected, but is not operating. For testing purposes, equipment in the dormant state may be cycled on and off. There is some evidence to show that on/off cycles can cause more damage than lengthy sotrage times.

In dormancy, however, there is usually an elimination, or at least a reduction, of the electrical and environmental stresses normally experienced in the operational state.

Harris [5] points out that many commercial items perceived as contmuously operating are truly in a dormant state for the greater portion of their useful lives. There may be cases of enforced dormancy. Electronic control systems are in place, but not being used, in various nuclear power plants. Prior to start-up, the effects of dormancy should be evaluated. Commercial equipment designers should consider the dormancy effect in their products.

Storage

Storage is defined as the state in which the system, subsystem, or component is totally inactiviated and resides in a storage area. The device may be packaged with special attention to preservation, and this packaging may provide a more benign storage environment for the device.

In some of the references [8 and 9], special effort was made to derive a .oK" factor which related dormancy/storage failure rates to operating failure rates. This "K" factor was not used in RAPC-TR-85-91, since the RAPC analysts did not make the assumption that operating and nonoperating failure rates are directly proportional.

RADC-TR-85-91 deals with the issue of dormancy versus storage by the addition of a "cycling factor." The cycling factor modifies the storage failure rate as a function of the number of times the equipment is turned on. The base storage failrue rate is increased by a multiplication factor due to cycling. The cycling factor accounts for the possibility of on/off cycles causing dama�e through additional stresses. If no cycling takes place, the deVIce has been in a true "storage" environment, and the cycling factor is unity.

With the methods of RAPC·TR-85-91, the analyst can calculate the total storage failllre rate for the device and predict if tlie creVice· mee1stne storage reliability goal. If the storage reliability goal is not predicted as being achievable, periodic testin� or pre-launch testing may be indicated. The advantages and dIsadvantages of such testing are compared with the results of no testing in references [7], [8J , [9], and [10]. The cycling factor accounts for the effects of periodic testing.

Certain types of components will exhibit a shelf life. This shelf life will be due to some physical degradation mechanism, caused by the component being sensitive to environmental stresses such as humidity, chemical content (e.g., of packing material), normal atmospheric pressure variation, radiation, microbes, and ambient temperature. If these storage.-sensitiv�_com.J>One'!ts are stor�� for long periods of

. time Wltli suffiCIent protection, the abilIty of the components to withstand operational stresses may be greatly reduced, due to the cumulative damage of storage failure mechanisms.

When components exhibit known storage degradation mechanisms, or have a known finite storage life, the analyst should press for the inclusion of a test prior to actuation and use of the device. If the test is 100% effective, all storage related failures are removed prior to using the device. The mathematics of test effectiveness are dealt with in references [8] and [9].

RAPC-TR-85-91 General Model

The RAPC-TR-85-91 storage failure rate model is patte�ned after the model of MIL-HDBK-217D. The general form IS:

Where: Ai> = the device nonoperating failure rate

ANb = the base nonoperating failure rate

f1NT = nonoperating temperature factor

nNE = nonoperating environmental factor

nNQ = nonoperating quality factor

ITcyc = equipment power on-off cycling factor

If the unit is never exercised during stora�e, or if the unit is seldom turned on, the cycling factor equals UDlty. With the exception of the addition of the cycling factor, this model is quite similar to the MIL-HDK-217D operational failure rate model, (see equation 2):

Where: Ai> = the part operating failure rate,

MIL-HDBK-217

Ab = the base failure rate for that kind of part

nE = environmental mode factor

ITQ = quality factor

ITS = other, special factors related to the type of part, such as operating stresses

MIL-HDBK-217D defines 26 different environmental factors, ranging from a low numerical value for the Ground, Fixed environment to a large numerical value for the high shock environments such as Cannon, Launch.

In a similar fashion, the quality parameter varies from a low numerical value (for high quality screening) to a high numerical value (for low quality parts).

This concept of assigning larger parameter values for harsher conditions, and lower values for more benign conditions, has been carried over to the methods of RAPC-TR-85-91.

In RAPC-TR-85-91, there are 26 environmental factors, corresponding exactly with the MIL-HDBK-217D factors. The RAPC-TR-85-91 models are modified to account for factors which are specific to each kind of component. For example, the temperature factor for integrated circuits ICs) is a function of the number of gates (digital ICs) or the number of transistors (linear ICs). A more complex Ie will have a higher temperature factor than a simple IC, resulting in a higher storage failure rate for the more complex Ie.

The classes of components addressed in RADC-TR-85-91 range from vacuum tubes to VlSI ICs. Quality levels range from commercial to Oass "s" for space applications. The "cycling factor" varies from unity for greater than 1000 hours between cycles, �o a high value for a mean-time-between­power-on cycles of 20 liours.

1989 PROCEEDINGS Annual RELIABILITY AND MAINTAINABILITY Symposfum 179

Example: Storaie Failure Rate: Component

Prior to using the RADC-TR-85-91 methods on Government contracts or on proposals, the methods were checked by comparison with data available in the literature. For example, Sandia National Laboratories, New Mexico, had prepared an extensive report on efforts to assess dormant storage reliability [10]. In the Sandia reference, sufficient information was presented to identify the kind and quality level of parts, the storage environment, and the number of on-off cycles involved. Some parts had been stored for almost 20 years, but the majority of the data was for a storage period of 8-10 years.

digitaJ J!�c����e����:�:���� ���P,,J�t�TI������!Il signal devices. Generally, the diodes were silicon metallurgically bonded devices. The capacitors were solid tantlum capacitors.

For comparison purposes, RADC-TR-85-91 storage failure rate calculations were made for simple components in a warehouse (Ground, Fixed Environment) at a storage temperature of 40·C. The high quality (Hi-Rei components) factor was chosen. Results are presented in Table I.

TABLE I

COMPARISON OF STORAGE FAILURE RATES

COMPONENT TYPE SANDIA VALUE RADCVALUE

SSI, IC 0.95 1.492 TRANSISTOR 0.46 0.475 DIODES 0.23 0.345 CAPACITORS, 1.8 0.432 �lid Tan�

ISTOR 0.18 0.183

(All failure rates are reported in FITs, failures in 109 hours.)

The SSI IC was considered to have four gates, and had gone through a MIL-STD-883, Gass "B" screen. The Sandia value-had been calculated for data from Pt;-P lI·,n)t� transistors, while the RADC value was calculated for NPN transistors, only. The RADC calculation was made for a silicon, general purpose signal diode. The quality of tantalum capacitors has improved since the Sandia paper was written, so the lower value for the RADC numeric may reflect that quality improvement.

In Ileneral, the RADC calculated values compare favorably WIth the data presented by Sandia.

Example: System

A sonobuoy is an expendable sensor system, designed to locate submarines in the ocean environment. Upon deployment, an lI('.QUStic.a! device is lowered from the sonobuoy to listen in the ocean depths for submarine noise. The sonobuoy then transmits the information, via a radio link, to a patrol aircraft.

Because of their expendable nature, sonobuoys are designed to "form, fit, and function" requirements. This means that the US Navy does not require a sonobuoy produced by one company to be a slavish replica of the design made by the original producer, but rather that the sonobuoy design will fulfill the form, fit, and function requirements for that particular model. It is therefore acceptable to compare the same model sonobuoys produced by different manufacturers.

Design informatiorrwas available on the Sippican version of the AN/SSQ-77A sonobuoy. RADC-TR-85-91 models were used to calculate a storage failure rate (1.738 failures per million hours) for the ANjSSQ-77A sonobuoy.

The Naval Weapons Support Center conducts a periodic stockpile assessment of sonobuoys, stored at various locations. Sonobuoys stored at the Naval Air Station, Moffett Field, California were recently assessed. (See reference [11] for complete details.) In total, 269 sonobuoys were tested. Two different sonobuoy manufacturers were involved. Storage time varied from 1-4 years. For ease of calculation, each year was assumed to be a full calendar year, from January 1st to December 31st. There were five reported failures, but the causes were not fully identified. The conservative assumption was therefore made that all failures were caused by storage mechanisms. No failure was censored. Total at risk time was greater than four million hours.

The CHI-SQUARED distribution, for a time truncated test, was used to calculate the lower and upper confidence limits on sonobuoy failure rate. Values for a confidence level of 90% are presented in Table II.

TABLE II

STORAGE FAILURE RATES (NSWC DATA) SONOBUOYSTORAGE

(Failures per million hours)

LOWER LIMIT POINT ESTIMATE

1.179

UPPER LIMIT

2.182 0.421

Thus, the calculated value of 1.738 failures per million hours for the predicted storage failure rate falls within the confidence limit values for a statistically significant test performed by an independent authority. This gives us reasonable confidence that the RADC storage failure rate calculation methods are acceptable for at least one class of electronics system.

Example: TWf

A Travelling Wave Tube (TWT) is a thermionic emission vacuum tube, useful at high frequencies. TWTs have high �ain, large bandwidth, and a frequency of operation which is easily oontrolled by electrical signals (as opposed to mechanically adjusted tubes). In general, a 1WT" will contain a cathode, an anode, input and output radio frequency (RV) couplin�, and some sort of focusing magnet. A wire helIX, called the ' slow wave structure," runs axially along the length of the tube. In today's designs, the vacuum tube is actually a metal tube, and much work has been done on the reliability of the ceramic-to­metal seals.

During storage, the major vacuum tube failure mechanism is a loss of vacuum. A1thouSh a microscopic vacuum leak may be present at storage mception, the tube might not fail until later. This kind offailure mechanism is indicative of a time increasing failure rate, which means that a vacuum tube could have a finite shelf life. However, for TWTs, the RADC volume stated,

" . .. Many high quality military tube types including TWTs and magnetrons are no longer believed to have a 'shelf life,' and thns, the operating failure rate could be aecurately assumed to be constant with time" [1]

180 1989 PROCEEDINGS Annual REUABIUTY AND MAINTAINABILITY Sympoalum

The RAOC-TR-85-91 TWf storage failure rate model is therefore simple:

Where: Ap = the predicted tube nonoperating

failure rate

ANb = nonoperating base failure rate

(3)

IIE = nonoperating environmental factor

For a TWf in a Ground, Fixed (warehouse) environment, the model yields a storage failure rate value of 2.07 failures per million hours.

.... . · '1'6 eValuate this caicuiated value r.VT storage failure rate, information was requested from TWf manufacturers and TWf users. Trips were made to three TWf ma�lUfacturers, who agreed with the RADC model for older desIgn TWfs.

A report which contained data on storage effects on TWfs [131 IS of special interest. A total of nine tubes were put into storage in 1965. Testing did not take place until March, 1984 with three failures noted. A failed tube may have suffered failure at the very beginnning of storage time or at the very end. The time of failure was therefore conservatively estimated by using half the calendar time accumulated on the failed tube.

The CHI-SQUARED distnbution was again used to calculate the lower and upper confidence limits. Values for a confidence level of 90% are presented in Table III.

TABLE III

STORAGE FAILURE RATES (AFWAL-TR-86-1123) [3] TWf

LOWER LIMIT

5.90

(Failures per million hours)

POINT ESTIMATE

2.64

UPPER LIMIT

0.969

The data support a "best" estimate of 2.64 failures per million hours; the RADC predicted value is 2.07 failures per million hours. The work in AFW AL-TR-86-1123 [131 was perf�rmed for the US Air Force and confirms the vabdity of the RADC model.

Future Model

The calculated values for TWf storage failure rates may be too conservative for modem TWfs. The manufacturers stated that computer-controlled processes (e.g., controlling the temperature for brazing) are used to produce modem TWfs, so the population of modem TWfs can be assumed to be significantly different that those referenced in the literature. Furthermore, modern TWf designs include a special "getter," which minimizes the effects of vacuum leaks. It is expected that future studies will show a TWf storage failure one-tenth to one-hundredth of the 2.07 predicted value.

Areas for Improvement

Environmental Factors

The RADC-TR-85-91 models use all the 26 ... ····· eriViioririiental faCf6iSliSted mMI�HDBK-217D. Tnis is

advantageous, as the reliability analyst familiar with MIL­HDBK-217 is automatically familiar with RADC-TR-85-91.

However, it is difficult to conceive of a situation where it would be necessary to calculate a stora"e failure rate for such a short­lived phenomenon as being launched from a cannon. The literal translation of MIL-HDBK-217 environmental factors to RADC-TR-85-91 models therefore results in a mathematical model which does not truly describe reality.

When special care, (such as special packaging) is taken to p.reserve an electronic system neither the Ground, Benign envIronment nor the Ground, Fixed environment accurately describ�s the storage environment. For example, sonobuoys are. typIcally s�ored in an "overpack" which provides both a mOls�ure ba!r!er and a barrier. to c�ntaminatin� gases. Usually, a d�slccant IS 1I�c1uded, and thIS drying agent WIll remove mOIsture r�sultlng from atmospheric conditions. Storage of a sonobuoy, In an overpack, in a c1imate- controlled warehouse results in an environment somewhat less harsh than Ground Fixed and more harsh than Ground, Benign.

'

When special attention is given to preservation techniques, the literal translation of MIL-HDBK-217 environmental factors to RADC-TR-85-91 models results in models which do not correctly describe the situation.

Surface Mount

. Defense Ele�tr.onics Supply Center (DESC), Dayton, Oh!o has been <juahfying surface mount components (chip reslstor.s and chip caracitors) for use in military projects. Only apprOlomately 5% 0 the Department of Defense electronic component espenditures is currently represented by surface mount components. It is expected that this will increase to approximately 40% during the next 5 years. The RADC-TR-85-91 storage models do not deal with surface mount components. Reliability techniques often lag technology.

� surfa�e mount resistor can be considered a through­hol� resIstor WIth two fewer solder joints. With a through-hole reslsto�, the act�al resistive element resides within the body of !h� resIstor and IS connected to the resistor leads by solder J�lnt�. The through-h!:!le resistor is then connected to a printed CITCUlt board by soldenng the resistor leads. There are two more solder jOints in a through-hole resistor as compared to a surface mount resistor. An electronic assembly made from surface mount passive components should be more reliable in storage than a similar assembly made from through-hole components since there are fewer solder joints to fail.

By this analogy, the surface mount passive component storage failure rate should be a fraction of the through-hole component storage failure rate. Based upon the analysis of the components' construction techniques, an adjustment factor, ranging from 0.5 to 0.75, has been proposed. The larger value 0.75, gives weight to concerns that the smaller surface mount

'

solder joints have less mechanical strength. As more data are accumulated on surface mount component storage, the RADC­TR-85-91 models should be adjusted accordingly.

Shelf Life

As an example, aluminum electrolytic capacitors are known to have a finite shelf life, which is a functIOn of the rate of expenditure of the electrolyte; the rate of expenditure is a function of the local ambient storage temperature and the purity of the aluminum used in the manufacture of the capacitor.

. . The models of RADC-TR-85-91 present a failure rate whIch IS constant over time. Mathematicallr, this is easy to �andle and reflects the physics of devices WIthout a known shelf life. However, the chances of storage failure of some devices (e.g., aluminum electrolytic capacitor) can best be described by a lognormal function, rather than an exponential with a constant failure rate.

1989 PROCEEDINGS Annual RELIABILITY AND MAINTAINABILITY Symposium lSI

Analysts should be aware that after a certain storage time, more and more aluminum electrolytic caeacitors will fail. The mean life time depends upon the care exhibited in

-- manufacturingthecapacitnr,-and the temperature history of exposure of the capacitor.

The RADC-TR-85-91 volume should be revised to provide a notice to analysts that other models may be needed after a certain storage time for certain components with known shelf lives.

Mechanical Components

The purpose of RACD-TR-85-91 was to deal with storage failure rates of electronic components. Mechanical components deserv.e the same t�eatment. Reference [?l provides storage failure rate estimates for nonelectroruc componnents . These values are point estimates based upon date for mechanical components. The single number, presented in Table IV, does not imply that mechanical components have a consta!lt sto�a$e failure rate: Typically, . mechanical components wIll exhibit a storage faIlure rate which will increase with time in storage.

TABLE IV

STORAGE FAILURE RATES NONELECTRONIC COMPONENTS IN GROUND, FIXED

ENVIRONMENT (Failure per million hours)

NONELECTRONIC COMPONENT

Bearings, Ball Bellows, General Gasket O-Ring Pumps, Fuel Valve, Fuel

(Adapted from reference [7])

FAILURE RATE

0.011 0.068 0.011 0.078 0.114 0.127

Comparison of a simple electronic component (a resistor in Table I at 0.00018 failures per million hours) with a simple mechanical component (a ball bearing in Table � at 0.011 failures per million hours) shows that the mecharucal component failure rate is. more than 60 times larger. . Comparison of Table I Wlth Table IV shows that nonelectroruc components have storage failure rates 60 to 600 times larger than simple electronic components. The scope of RADC-TR-85-91 should be expanded to include mechanical, nonelectronic components.

Conclusjons

The use of a new volume, RADC-TR-85-91, for the calculation of storage failure rate of electronic components has been examined. Analysts who are familiar with MIL-HDBK-217D methods will find it easy to work with the models of RADC-TR-85-91.

By the application of statistical techniques to data from the literature, the RADC-TR-85-91 models have been validated, for compC!nen�, systems, and special elect�onic devices. Some defiCienCies have been noted; these Wlll undoubtedly be resolved in future revisions of RADC-TR-85-91. It is recommended that reliability analysts make use of these RADC methods when calculation of storage failure rates are required.

References

[1] Coit, D.W. and Priore, M>G>, RADC-TR-85-91, � of Nono eratin Periods on ui ment Reliabili , Rome Air Deve opment Center, orne NY, May, 1985

[2] Bazovsky, Igor, Reliability Theo(Y and Practice, Prentice Hall, Inc., Englewood Qiffs, NY, 1%1

[3] MIL-HDBK-217D, Military Handbook, Reliabiliity Prediction of Electronic Equipment, Notice 1, dated 13 June, 1983

[4] NPRD-3, Nonelectronics Parts Reliability Data, Rome, NY, Summer, 1986

[5] Harris, A.P., "Reliability in the Dormant Condition," Microelectronics and Reliability. Vol 20,FP 33-44 (1980)

[6] Bauer, J., et aI., "Dormancy and Power On-Off Cyclin� Effects on Electronic Equipment and Part Reliabhlity," AD-768-619, RADC, Rome, NY, August, 1973

[7] Cottrell, D.F., et al., "Effects of Dormancy on Nonelectronic Components and Materials," ADIA-002 838, October, 1974

[8] Cottrell, D.F., "Dormancy Effects on Nonelectronics," Proceedines 1977 Annual Reliablili� and

aintainabili S m osium IEEE, 7RMOOI [9] Martinez, E. c., I torage Reliability with Periodic Test,"

Proceedines 1984 Annual Reliability and Maintainability Symposium. IEEE

[10] Merren, G.T., "Dormant Storage Reliabiilty Assessment­Data Based," IEEE Transactions on ComVcinents. Hybrids and Manufacturine Technol0eY, 01 CHMT-4, No. 4, December 1981, pp 446-454

[11] Pulliam, J.H., "Sonobuoy Stockpile Inventory Assessment Report of NAS Moffett Field," Naval Weapons Support Center, Crane, Indiana, Report No. 7056-86-011, November, 1986

[12] O'Connor, Patrick D.T., Practical Reliability Eneineerine. Heyden & Son, Ltd., London, Philadelphia, 1981

[13] Wilson, D.C. Jr., "Investigation of TWT Arcing, Outgassing and Processing for Life and Reliability," AFWAL-TR-86-1123, Varian Associates, Palo Alto, CA, December 1986

Bioeraphies

John P. Rooney, Sr. Member IEEE Sippican, Inc. 7 Barnabas Rd. Marion, MA 02738 USA Phone: (508) 748-1160x384 (work)

(508) 224-8156 (home)

For the past 3 years, John Rooney has been Reliability Manager at Sippi can, Inc., a mll:nufacturer of ocean,?gr�phic instruments and sonobuoys. Pnor to that, he was Pnnclpal Reliability Engineer at Data General, Westboro, MA and Principal Reliability Engineer at the Foxboro Company, Foxboro, MA. Mr Rooney was employed for almost 15 years at the Foxboro Company, a manufacturer of process control computers.

John Rooney has written and presented numerous papers on the subject of reliability, computers, and corrosion. He is a ' Senior Member of both the ASQC and the IEEE. He holds a BEE from Manhattan College ('65), and an MSEE for Engineering from Newark College (,69), now known as New Jersey Institute of Technology. He reSides in Plymouth, MA where he is a member of the Town of Plymouth, Committee on Nuclear Matters, dealing with Pilgrim I, Nuclear Power Plant.

Note of Appreciation

The author wishes to express his appreciation ot Maureen Martowska for her work in editing and completing this paper and to Howie Mott, VP Quality control, for his support. A special thanks to Gloria Mandurrago, Varian Associates, Palo Alto, CA for discoverin� some inconsistencies in the use of the CHI-SQUARED functIOn.

182 1989 PROCEEDINGS Annual RELIABILITY AND MAINTAINABILITY Symposium