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The sustainment of Department of Defense (DoD)

materiel is becoming increasingly vital as systems and

equipment remain in operation, surpassing their intended

lifetimes. As continually creeping, and in some cases rapidly increasing maintenance costs are realized, new maintenance methods are implemented to moderate and potentially reduce these financial burdens

while improving readiness. The latest

maintenance strategy, condition-based

maintenance plus (CBM+), aims to

integrate new concepts and long standing maintenance

processes and analysis methods with current state-of-the-art

technology and system engineering.

DoD Instruction 4151.22, signed December 2, 2007,

instituted the DoD policy that CBM+ be included in the

selection of maintenance concepts for all new weapon

systems, equipment, and materiel programs. In addition,

this Instruction requires the implementation of CBM+ in

current systems, equipment and materiel where it is “technically feasible and beneficial”.[1]

CBM+ is the application and integration of appropriate

processes, technologies, and knowledge based capabilities

to improve the reliability and maintenance effectiveness

of DoD systems and components. At its core, CBM+ is

maintenance performed on evidence of need provided

by reliability centered maintenance (RCM) analysis and

other enabling processes and technologies [hardware,

software, design, processes, communications, tools, and

functionality]. CBM+ uses a systems engineering approach

to collect data, enable analysis, and support the decisionmaking processes for system acquisition, sustainment, and

operations.[1]

There are two basic maintenance categories: reactive and

proactive. Reactive, which is also known as corrective maintenance, “is performed for items that are selected to run to

failure or those that fail in an unplanned or unscheduled

manner.”[2] “Proactive maintenance is considered either

preventive or predictive in nature, and the maintenance

performed can range from an inspection, test, or servicing

to an overhaul or complete replacement.”[2] The implementation of CBM+ is another step in the transition from

reactive maintenance to proactive maintenance. CBM+ is

intended to optimize materiel readiness in terms of materiel

availability, materiel reliability, mean downtime, and ownership costs.

Perhaps the most beneficial application of CBM+ is to

aviation systems, which have rigorous maintenance and

inspection requirements. According to a 2009 Army

Posture Statement, “the aviation community, where aircraft

are highly sensored, has been very active in the application

of the enablers required for CBM+.”[3] However, an area

that has been elusive in terms of effectively and accurately

acquiring meaningful data is the detection and quantification of corrosion. The feature article in this issue offers a

critical assessment of one specific type of corrosion sensor,

which was tested on various Army helicopter platforms.

There are a number of excellent resources that offer more

information on CBM+, including the CBM+ DoD

Guidebook,[2] which was developed by the CBM+ Action

Group (http://www.acq.osd.mil/log/mpp/cbm+.html). In

addition, the US Army Logistics Innovation Agency

(USALIA) is aiming to publish its Condition-Based

Maintenance Plus (CBM+) Implementation Plan this year.[3]

While it is still too early to realize condition-based maintenance’s full potential for the DoD’s wide variety of physical assets, the Department is on a path to where maintenance will connote prevention rather than repair.

Ben Craig, Editor

[1] “Condition Based Maintenance Plus (CBM+) for Materiel

Maintenance,” DoDI 4151.22, USD(AT&L), December 2, 2007,

http://www.acq.osd.mil/log/mpp/cbm+/docs/DoDI_415122.pdf.

[2] “Condition Based Maintenance Plus DoD Guidebook,”

CBM+ Action Group, May 2008, http://www.acq.osd.mil/

log/mpp/cbm+/CBM_DoD_Guidebook_May08.pdf.

[3] “Condition Based Maintenance Plus,” 2009 Army Posture

Statement, http://www.army.mil/aps/09/information_papers/

condition_ased_maintenance_plus.html.

An Ounce of

Prevention...

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http://ammtiac.alionscience.com The AMMTIAC Quarterly, Volume 4, Number 2 3

ABSTRACT

The Army conducts annual inspections of all helicopters to determine which aircraft require depot level maintenance. The inspection includes collecting corrosion data to identify weaknesses in

the design and maintenance of the airframes. An effort is underway

to supplement the inspections with sensors that may assist in the

prediction of corrosion related maintenance activities. A study was

conducted on helicopters to determine if sensors could be securely

attached to the exterior surfaces and if the sensors could be used to

determine corrosion rates. The study concludes that sensors can be

flown on helicopters; however sensors alone are not an effective tool

in determining corrosion rates.

INTRODUCTION

A recent study performed for the Department of Defense (DoD)

estimates the annual cost of corrosion to the US Army’s aviation and

missile weapons systems to be $1.6 billion.[1] The cost of corrosion

to the military is so significant, Congress enacted legislation to

reduce corrosion and its effect on military equipment and infrastructure.[2] The highest contributors to Army corrosion costs are

helicopters.[1] The OH-58 Kiowa, the UH-60 Blackhawk and the

CH-47 Chinook helicopters account for an estimated $1.1 billion

in annual corrosion related maintenance costs.

As a result, new technologies are being developed such as helicopter rinse stations and corrosion preventative compounds to help

mitigate the effects of corrosion, thereby reducing maintenance

costs. Evaluating the effectiveness of these new technologies is very

important.

One sensor technology is being used to study the effectiveness

of rinsing helicopters.[3] Although the results are inconclusive at

this time, it is hoped that expanded use of these sensors will help

develop a condition-based maintenance program to predict maintenance activities on helicopters.

Background

The US Air Force has studied the effects of corrosion on aircraft

for many years and has determined that one of the most common

forms of corrosion in aircraft structures is uniform corrosion.[4, 5]

Uniform rates of corrosion are generally measured in loss of material thickness per unit time. One common form of a corrosion-rate

expression is inches per year (in/yr) and the loss of thickness can

be calculated by the mass loss. Relating the mass loss to time, an

expression can be written as follows:

w in/yr = ––––– (1) dSAt

where w is the mass loss, d is the density of the material, SA is the

area of exposure and t is the time of exposure. If w is expressed in

milligrams, d in grams per cubic centimeter, SA in square inches and

t in hours, then using the appropriate conversions, the corrosion

rate can be rewritten in terms of mils per year (mils/yr):

534w mils/yr = ––––– (2) dSAt

This common form of corrosion rate is a generally accepted expression.[6]

The Air Force and the Navy have used the Cumulative

Environmental Corrosivity (CEC) sensor for several years. The Air

Force has installed the CEC sensor within the interior of different

airframes, such as the C-130 and UH-60, to study the effects of

corrosion.[7] The Navy has used the same sensor on interior surfaces of the P-3 aircraft. The Army believes that the use of these

sensors on aviation and missile systems might aid in predicting

corrosion related maintenance. Furthermore, the Army is interested in attaching and flying these sensors on aircraft exteriors to

study the effects of aircraft rinsing.

The CEC sensor is passive and is composed of a thin copper

strip (approximately 99% pure) embedded in a fiberglass reinforced

plastic board. The sensor is shown in Figure 1.

A visual inspection

of the sensor shows that

the copper traces are

oriented in a fashion

very similar to a wheatstone bridge. Thus, the

sensor can be modeled

as a wire.

The resistance of a

material depends on the

resistivity of the material and the geometry

Steven Harrigan.

University of Alabama in Huntsville

Huntsville, AL

Figure 1. Cumulative Environmental

Corrosivity sensor.

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of the current path through it.[8] All metals exhibit the intrinsic

property of resistivity. The typical value of copper resistivity, ρ, (at

68°F) is approximately 0.669 x 10-6 Ω-inch. The resistance, R, of a

wire can be expressed in the following form:

ρl R = ––– (3) A

where A is the cross-sectional area of the wire and l is the length. As

the material corrodes the cross-sectional area will decrease resulting

in an increase in resistance. It is believed that the sensor output is

similar to the resistance measurements detected in a wheatstone

bridge.

These sensors, along with metal coupons, have been placed at

numerous sites around the world. Although some initial relationships have been made between sensor output and the corrosion of

metal coupons, no conclusive models have been published.[9] The

sensor output is a unitless number.

Research Objective and Methodology

The purpose of this paper is to determine if the sensors are an

effective method for gathering environmental exposure data on helicopters and, if so, whether any statistical inferences can be made

concerning corrosion rates. The methodology includes an assessment of the field data and laboratory testing:

• Determination of sensor placement on the aircraft

• Analysis of the helicopter sensor data

• Laboratory testing results

• Conclusions/recommendations

ANALYSIS

Aircraft Condition Evaluation Program

The Army has been collecting airframe data as part of the Airframe

Condition Evaluation (ACE) Program since 1975.[10] The ACE

program, now known as the Joint Airframe Condition Evaluation

(JACE) program, seeks to identify airframes that require corrective

depot-level maintenance action.[11] The evaluation consists of a

visual inspection utilizing established criteria in order to make an

objective assessment for maintenance actions. Included in the JACE

inspection is an evaluation of airframe corrosion in order to identify and quantify corrosion data across all airframes and to look for

trends for the prevention and abatement of corrosion. The annual

inspection is performed by a two-person team on virtually every

helicopter in the Army. The current helicopter fleet is composed

of six different airframes and a total of over 3500 aircraft.

The JACE program records counts of corrosion ‘hits’ in different

areas on the airframe. A hit is defined as any visual indication of corrosion activity such as galvanic, general or pitting corrosion. Table 1

shows the percent of corrosion hits for the various airframes and

locations inspected

in 2007.

Table 1 shows the

highest percentage

of corrosion hits to

be on the top of the

CH-47 and OH-58

aircraft. The side and

underside locations

(and the UH-60

top) appear to have

a similar number

of corrosion hits. The UH-60 historically has a lower number of

corrosion hits.[10] The location shown in Table 1 is a generalization

of the area of the helicopter that had specific corrosion hits. This

generalized data can be further broken down into a specific location

on the airframe. It is inferred from the JACE data that

the underside and side of the airframes have a lesser number of corrosion hits than the top of the airframe. A report, generated for the

three airframes listed in Table 1, was used to determine the specific

attachment point locations for the CEC sensor. It was anticipated

that field readings of sensors would support the conclusions of the

JACE inspections: the tops of the airframes experience a greater

number of corrosion hits.

Army Aviation and Missile Command Corrosion Program

Management Office Study

A study was conducted on Army helicopters based at Wheeler Army

Air Field (AAF), Hawaii, during January through August 2006.[12]

The study had two objectives. The first objective was to determine

if sensors could be attached to the exterior surfaces of operational

helicopters. This was risky because if a sensor failed to adhere during flight, it could become a high-speed projectile and catastrophic

damage could occur should the sensor strike a rotating mechanism,

such as a blade, or be ingested in the engine. The second objective

was to study the effects of rinsing helicopters exposed to a marine

environment (Wheeler AAF is approximately 8 miles from the

north shore of Oahu).

In this study, three different helicopter Mission Design Series

(MDS) platforms had CEC sensors attached in different corrosion

‘hot-spots’. These corrosion-prone locations were determined based

on the results of the JACE program. Sensors were attached to external surfaces of CH-47, OH-58 and UH-60 MDS aircraft in these

corrosion-prone areas. The sensors were attached to the exterior

paint using a 2-part epoxy system. This was to study the direct

effects of aircraft rinsing on the exterior surfaces. Although the

results of rinsing aircraft are inconclusive at this time, the study

did demonstrate that sensors can be securely attached to exterior

surfaces of operational helicopters.

Table 2 shows the

MDS, the sensor

location and the

sample size (i.e.,

number of sensors

used).

The analysis presented in this study

examines the data

from the first 41 days of sensor exposure on the Wheeler aircraft.

The Wheeler report indicates all but one of the sensors had an

increase in output.[3] It is well established that this increase is

directly attributed to the corrosion of the copper strip on the sensor.

The report shows each individual sensor rather than grouping all the

data to make inferences on the population.[3] The analysis presented in this article differs from the work presented in the report in that

the data is grouped by airframe and location. An initial analysis of

the data is shown graphically by use of a boxplot in Figure 2.

It is seen that CH-47-T (top), the UH-60-S (side) and the OH58-U (underside) show the greatest amount of dispersion in the

data. The cause for the large variation is unknown. It is expected

4 The AMMTIAC Quarterly, Volume 4, Number 2

Table 1. JACE corrosion hits data.

Airframe Location Percent corrosion hits

CH-47 Side 1%

Underside 5%

Top 8%

OH-58 Underside *

Side 2%

Top 19%

UH-60 Underside 0%

Side 4%

Top 6%

*Note: There is no data available for the OH-58 underside.

Table 2. Helicopter type and sensor location.

MDS Location Sample Size

CH-47 Side (S) 8

Top (T) 8

Underside (U) 8

OH-58 Side (S) 7

Underside (U) 7

UH-60 Side (S) 6

Top (T) 6

Underside (U) 6

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that the top surfaces (CH-47-T and UH-60-T) would have the

highest median sensor output, as the corrosion mechanism known

as time of wetness (TOW) would suggest surfaces which are subjected to standing water or that promote the formation of dew

should experience higher corrosion rates.

For the sensors to be effective, the variance in the data should be

understood and minimized if possible. An interview was conducted

with a subject matter expert as to why there might be such a large

variance in the data, and it is noted that some of the CH-47 airframes conduct fire control operations and may have been exposed

to salt water spray during fire fighting activities. It is unknown if the

specific CH-47 airframes were used for these missions. It was also

explained that the OH-58 aircraft are typically hangared at night

and on weekends. This sheltering of aircraft from the elements is

suspected to have a lessening effect on the sensor readings, however

the OH-58-U readings do not support this expectation.

A more detailed statistical analysis was performed on the data to

look for any differences in the groupings. It is believed that the

TOW is a critical factor in the sensor output. Sensors on the top

are expected to have higher sensor output than sensors on the side

and underside. Two questions are posed: 1) Can the sensors distinguish differences in orientation (location)? and 2) Can sensors

detect differences within the same airframe? With this in mind,

two hypothesis tests are performed:

• Hypothesis #1: All sensors in similar locations between airframes will have similar readings.

• Hypothesis #2: All sensors on similar airframes have similar

readings.

All data was subjected to normality testing. The CH-47 underside, OH-58 underside and side, and the UH-60 underside and

top data all follow a normal distribution. The remaining data do

not follow a normal distribution. Since most of the data are not

normal and because of the small sample size, a statistical analysis

was performed using a nonparametric method. The KruskalWallis analysis of ranks hypothesis testing was used to look for

differences in population medians.[13]

The assumptions used for this test are as follows:

• All samples are randomly and independently drawn from the

same population of helicopters.

• All samples have approximately equal variances (this assumption was checked using Levene’s Test).

• There are at least five observations (test statistic is approximated by a chi-squared distribution).[14]

• Significance level is α=0.05.

If the test statistic (H) falls in the critical region H>χα

2 with

ν=k-1 degrees of freedom, then a rejection of the hypothesis at

the α=0.05 level of significance will be the result; otherwise the

hypothesis will not be rejected.

As seen in the boxplot, the underside sensor output readings

appear to be different and the side and top readings appear to be

similar. Table 3 shows the results of the Kruskal-Wallis tests.

Based on the analysis, the side and the top readings are not

significantly different across the three MDS; however the underside readings are statistically significant. Returning to the boxplot

in Figure 2, it is seen that the OH-58 underside sensor output is

significantly different from the CH-47 and UH-60 underside

sensors. This should be a major area of focus as to why the

OH-58 underside experiences such a difference. Table 4 shows the

results of the Kruskal-Wallis tests for the three different airframes.

The hypothesis testing on the CH-47 indicates there is no statistical difference between the sensor output for the top, side and

underside at the α=0.05 significance level. The calculated p-value

shown does not make a very strong argument for not rejecting the

hypothesis. Although the Kruskal-Wallis hypothesis test is useful

for small samples, a careful review of the data and a consideration

of sample size are needed before a ‘fail to reject’ conclusion is made.

It does appear from the data that the different areas of the OH-58

and UH-60 MDS are statistically different. This means that the

different areas of the same aircraft may require different mitigation

strategies. A strategy for the top of the airframe might be different

than a strategy for the side or underside of the airframe.

Finally, the sensor data is compared to the JACE corrosion hits

data. Table 1 was compared against the sensor field data shown in

Table 5. The results in Table 5 indicate that the sensor output is similar to the anticipated conclusions of the JACE data with the exception of the UH-60 top readings. The cause for the unexpectedly

high readings on the UH-60 top is unknown. It does appear that

the underside and the sides of the airframes experience a lesser

amount of corrosion than the tops.

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Figure 2. Boxplot of helicopter data.

CH-47-S CH-47-T CH-47-U OH-58-S OH-58-U UH-60-S UH-60-T UH-60-U

MDS and Location

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.0

Sensor Output

Table 3. Table of sensor location hypothesis testing across the

airframes.

Hypothesis #1 Sensor Location

Underside Side Top

Test Statistic (H) 9.83 0.71 0.00

Degrees of Freedom 2 21

N 21 21 14

P-Value 0.007 0.702 1.00

χα

2 Value 5.99 5.99 3.84

Result Reject- Do not Do not

readings reject reject

are different

Table 4. Table of sensor location hypothesis testing within the

airframes.

Hypothesis #2 Helicopter

CH-47 OH-58 UH-60

Test Statistic (H) 5.00 5.59 10.19

Degrees of Freedom 2 12

N 24 14 18

P-Value 0.082 0.018 0.006

χα

2 Value 5.99 3.84 5.99

Result Do not Reject Reject Reject

Boxplot of Day 41 vs MDS and Location

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Although the statistical analysis may be useful for the airframes that conduct similar operations (it is assumed that the similar airframes were exposed to similar conditions), a look at the

individual airframe data is worthwhile. Figure 3 shows the sensor

readings for all the CH-47 aircraft. The Airframe Number represents the aircraft serial number and is in no particular order.

It appears that the sensors on the individual CH-47 airframes

show similar patterns. Spearman’s

rank correlation coefficient (SRCC) was

calculated for the top,

side and underside as

shown in Table 6.

This method was

used in lieu of

Pearson’s coefficient

because of the nonparametric nature of

the data.

It appears as though there is sufficient evidence that the correlations are not zero and that a linear relationship may exist between

the sensor output and the different areas of the CH-47 aircraft.

Although there is a positive correlation of the data, airframes 2, 3,

4 and 7 seem to show different outputs than do airframes 1, 5, 6

and 8. The exact cause of the difference is unknown. These two

different sets of aircraft may have experienced different operational

mission profiles or they may have experienced different environmental exposures.

The OH-58 data by airframe number is shown in Figure 4. The

airframe number underside readings appear to follow patterns similar to the side readings (greater in all cases) with the exception of

airframe numbers 3 and 8. Airframe number 3 has an underside

reading of -0.005 and was removed from the data. It is suspected

to be a bad reading as all other sensors showed some increase over

the exposure time period. Airframe number 8 underside reading

appears to be a major outlier in the data. The reason for this high

reading is unknown. The Pearson correlation coefficient value is

0.344 (p-value =0.505). This does not show a strong correlation

of the data. Additional data is needed and the large departure of

the underside sensor output for airframe number 8 needs to be

understood.

The UH-60 data by airframe number is shown in Figure 5. It is

seen that the sensor output shows similar patterns across the different airframes except

for the side readings

for airframes 4 and

5. The cause of these

unusual deviations

from the pattern is

unknown. The SRCC

was examined to look

for evidence of a correlation of the data as

seen in Table 7.

Although some

evidence of a positive

correlation exists

between the side and

the underside readings, the correlation

is not very strong.

Additional information is needed to

determine why the

side readings for airframes 4 and 5 are so

different from the

other side readings.

Overall, the sensor output for the different airframe numbers

within the particular MDS is fairly consistent except as noted.

Sensor readings in all areas are fairly uniform. What is unknown

is if the particular airframe number (example would be UH-60

airframes 4 and 5) would see the same corrosion when inspected in

the JACE program. The sensor output for these specific airframes

should be coupled with the next JACE evaluation to see if any

relationships can be made.

Laboratory Testing

It is known that time of wetness is a critical variable with respect to

corrosion.[15] A surface that is in constant contact with an electrolytic solution will inevitably have a higher corrosion rate than a

surface that is absent of an electrolyte. This time of wetness factor

must be taken into account when examining the results of the JACE

program and the Wheeler AAF data. It is suspected that this factor

(along with the environment) may contribute more to corrosion

than airframe type or mission. With this in mind, two laboratory

exposure tests were conducted to examine these effects.

One exposure was an accelerated temperature/humidity test

(Modified MIL-STD-810F, Method 501 and 507) and the other

exposure was salt fog (ASTM E117). Sensors were placed in environmental chambers and subjected to controlled conditions. The

temperature/humidity exposure was 85°C and 85% relative humidity; the salt fog exposure was 35°C with 5% salt solution. All sensors had the same orientation (approximately 45 degrees to the horizontal). As expected, the salt fog exposure was much more severe.

6 The AMMTIAC Quarterly, Volume 4, Number 2

Table 5. Sensor output data.

Rank Order Lowest-Highest: Day 41 Sensor Median Output (x100)

CH-47-U 7.05

UH-60-U 7.15

CH-47-S 10.70

OH-58-S 13.50

UH-60-S 14.45

OH-58-U 25.50

CH-47-T 32.60

UH-60-T 36.80

Figure 4. OH-58 airframe sensor readings.

Table 6. CH-47 Spearman’s rank correlation coefficient matrix.

Coefficient CH-47 Side CH-47 Top

CH-47 Top 0.906 -

CH-47 Underside 0.897 0.889

Figure 5. UH-60 airframe sensor readings.

Table 7. UH-60 Spearman’s rank correlation coefficient matrix.

Coefficient UH-60 Side UH-60 Top

UH-60 Top 0.448 -

UH-60 Underside 0.615 -0.083

123 45 67 8

Aircraft Number

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.0

Under

Side

Sensor Output

123456

Aircraft Number

0.6

0.5

0.4

0.3

0.2

0.1

0.0

Under

Top

Side

Sensor Output

Chart of OH-58 Data by Location and Aircraft Number

Location

Chart of UH-60 Data by Location and Aircraft Number

Location

Figure 3. CH-47 sensor output.

1 2 3 45 6 7 8

Aircraft Number

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.0

Top

Under

Side

Sensor Output

Chart of CH-47 Data by Location and Aircraft Number

Location

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It is conclusive that the sensors respond much differently to marine

environments than to hot humid environments as seen in Figure 6.

Additionally, the sensors were exposed to salt fog at orientations

similar to those experienced on the various airframes as shown in

Figure 7. The top exposure was face up at 0 degrees to the horizontal, the side exposure was at 90 degrees

to the horizontal and the underside

exposure was face down (180 degrees

from the top exposure).

The results shown in Figure 7

appear to follow the results of the field

exposure where the upper helicopter

sensors experienced higher sensor output readings than the side and underside of the airframe. This is likely due

to the surface maintaining contact

with a corrosive electrolyte (5% salt

water). The laboratory salt fog testing

appears to support the notion that the

time of wetness is a key factor.[5] The

negative slope experienced between

100 hours and 144 hours of exposure

is unexplainable at this time but is

believed to be the result of short circuits occurring due to a build-up of

electrolytic compounds on the surface

of the sensor. Future laboratory testing

should include a gage reproducibility

and repeatability study on the sensors.

An additional test was performed

to determine if the sensor output

could be related to the corrosion of

metal. Four different metals were

exposed to salt fog along with the

sensors. Copper (~99% pure), magnesium (ZK41), aluminum (7075)

and steel (4340) are common alloys

used on helicopters. These coupons

were exposed for three different durations (48, 96 and 144 hours). Three

coupons of each metal were exposed

for each duration. The coupons were

prepared, tested and analyzed per a

standard testing protocol.[6]

The corrosion rate expression

(equation 1) using the variables

weight loss, time and surface area were

measured and weight loss/surface area,

Λ, was graphed against time as shown in Figure 8. All alloys

showed an increase in the rate of corrosion as the length of exposure increased. This exposure is the salt fog exposure in Figure 6.

This is significant as it may be possible to develop a corrosion rate

model based on sensor output, environmental exposure (marine,

industrial or desert) and alloy type.

CONCLUSIONS

Cumulative Environmental Corrosivity sensors show a response

when exposed to the environment. The extent of the response

depends on the type of environmental exposure and the orientation.

Laboratory testing shows the sensors respond differently to a hot

humid environment than to a salt fog environment. It is also seen

that the sensors respond differently based on their orientation. The

orientation of the sensor (time of wetness) is known to be a key

parameter. A surface that is oriented to remain wet with an electrolyte will experience more corrosion

than a surface that promotes electrolyte

runoff. The most severe exposure

detected by the sensors on the Wheeler

helicopters occurs on top of the helicopters. The 2007 JACE data seems to

support this, as a higher number of

corrosion hits on the top of the CH-47

and the OH-58 were recorded.

Laboratory testing of the sensors indicate orientation contributes to differences in sensor output, as it is seen that

the top exposure results in higher sensor output at every duration (except as

shown in Figure 7).

The laboratory testing combined

with the JACE data and the field data

support the conclusion that time of wetness is a key factor in detecting general

corrosion. Should the Army accept this

conclusion, they may find that an effective method of protecting equipment

exposed to a marine environment can be

accomplished by covering or sheltering,

thereby reducing the time of wetness.

Laboratory testing also confirms that

sensors exposed to a salt fog (marine)

environment exhibit a greater amount of

sensor output than those exposed to elevated temperature and humidity.

Although this is no great revelation, the

Army could potentially save time and

effort in how they perform maintenance

on equipment located in desert environments as opposed to marine environments. Equipment that uses a timebased maintenance (with respect to corrosion related maintenance) evaluation

could be replaced with a conditionbased evaluation with the aid of sensor

technology. Laboratory testing shows

evidence that a correlation exists

between orientation and sensor output;

the CH-47 also shows similar evidence. If the cause for the unusual

sensor readings for the OH-58 and UH-60 (Figures 3 and 4) can be

determined, it may be possible to derive a relationship between area of

exposure (location) and corrosion related activities on helicopters.

Furthermore, it may be possible to determine a corrosion rate based on

the output of a single sensor, as correlation appears to be strong in the

case of the CH-47 aircraft.

Knowing the type of environment and the time of wetness are

key factors in corrosion, it is apparent that the concept of rinsing

helicopters with clean water in a marine environment is a good

practice.[5] The Army should pursue this technology, however

Figure 6. Sensor output for differing laboratory

exposures.

Figure 7. Sensor output for laboratory exposure at

differing orientations.

Figure 8. Gamma versus alloy and time.

0 100 200 300 400

Hours

0.5

0.4

0.3

0.2

0.1

0.0

Sensor Output

Scatterplot of Sensor Output vs Hours

50 75 100 125 150 175 200

Duration (hrs)

1.4

1.2

1.0

0.8

0.6

0.4

0.2

0.0

Side

Top

Under

Sensor Output

Scatterplot of Reading vs Duration (hrs)

Orientation

Time (hrs) 48 96 144 48 96 144 48 96 144 48 96 144

Alloy Aluminum Copper Magnesium Steel

1200

1000

800

600

400

200

0

Gamma = (Weight Loss/Surface Area)*10000

Interval Plot of Gamma vs Alloy and Time

95% CI for the Mean

Exposure

Salt Fog

Temp/Humidity

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8 The AMMTIAC Quarterly, Volume 4, Number 2

further analysis is required to determine the effects. This further

analysis should include putting sensors on both rinsed and unrinsed

helicopters in the same environment at the same time.

RECOMMENDATIONS

There is a great amount of variance in sensor output within airframes

and between airframes. This variance may be due to the differences

in how the helicopters are operated or it may be the sensitivity of

the sensors. In the future, records should be provided with the

sensor data showing flight profiles, maintenance practices and geographical location to determine if these factors result in differences in

sensor output. A gage study should be performed on the sensors.

As seen in Figure 4, one of the OH-58 underside sensors showed a

negative sensor output and this is not believed to be accurate.

The sensor output should be coupled with the next JACE

inspection of these airframes. A relationship may be formed

between corrosion hits and sensor output, which would be

extremely useful in predicting corrosion when a predetermined

sensor output is reached. This could potentially reduce or eliminate

JACE corrosion inspections in the future.

It may be helpful to move the sensors to different locations on

the airframes, which would be useful in optimizing the location of

sensor placement to maximize the effectiveness of detecting environmental exposure. This movement may help explain why the

OH-58 underside showed a greater sensor output than expected

when compared to the other airframes and the JACE data.

It is recommended that additional laboratory testing on the

sensors be conducted for industrial pollutants. A standardized test

exists (ASTM G85) that may help determine the effects of hydrogen sulfide compounds on the sensors. It is known that industrial

pollutants have a great effect on corrosion rates.[5] This may assist

maintenance officials in the placement of gasoline and diesel

powered support equipment to reduce the deleterious effects of

industrial pollutants or the location of airfields with respect to

surrounding industries and prevailing winds.

Future employment of these sensors should utilize the basic tenants of good industrial engineering practices. Implementing the tools

of Six Sigma, especially with respect to measuring the existing conditions, will help establish the metrics and benchmarks from which

improvements can be judged.[16] Without a reference value for the

‘pre-rinsed’ helicopters, it will be difficult to show the effectiveness of

the clear water rinse system. A statistically designed experiment

would help the Army understand which factors (MDS, geography,

time of wetness, pollutant) have the greatest effect on corrosion and

what interaction is present. If the experimental error can be quantified, confidence in the results and the correct solution can lead to

cost savings that can be used in other areas of military readiness.

Future contracts with the sensor manufacturer should include

requirements for information on how the sensor technology

works, full access to the reader and a quantification of what the

sensor output means.

Finally, the development of a system model may help the Army

to determine inspection frequency as it relates to major pollutants

and geography. It is known that copper forms a variety of patinas

when exposed to different environments.[17] An inspection of the

sensor surface contaminants (whether visual or chemical) may indicate the primary constituents to be chlorides, sulfides or oxides.

This information may lead to a different maintenance strategy based

on the type of contamination.

ACKNOWLEDGEMENTS

Mr. Steven F. Carr, AMCOM Corrosion Program Manager –

AMCOM Corrosion Program Office; Mr. Shanon P. Dunlap, Senior

Engineer Analyst; Mr. James W. Roberts, Senior Engineer Analyst,

Science Application International Corporation; Dr. Sampson

Gholston, Associate Professor, University of Alabama in Huntsville.

REFERENCES

[1] Herzberg, E. F., R. W. Durant, D. A. Forman, N. T. O’Meara, O. R.

Thompson, J. C. Tran, E. D. Turner, and E. R. Wingrove III, “The Annual

Cost of Corrosion for Army Aviation and Missile Equipment,” LMI,

Report SKT50T3, June 2007.

[2] “The Bob Stump National Defense Authorization Act for Fiscal Year

2003,” Public Law 107-314, December 2002, p. 201.

[3] Abbott, W. H., “Final Report on Corrosion Sensor Studies on Army

Helicopters – Wheeler AAF,” August 2006.

[4] “Modernizing the Army’s Rotary-Wing Aviation Fleet,” Committee on

Aging of U.S. Air Force Aircraft National Materials Advisory Board

Commission on Congressional Budget Office, November 2007.

[5] “Aging of U.S. Air Force Aircraft - Final Report,” Engineering and

Technical Systems National Research Council, Publication NMAB-488-2,

National Academy Press, 1997.

[6] Fontana, M. G., and N. D. Greene, “Corrosion Engineering,” 2nd

Edition, McGraw-Hill, 1978.

[7] Abbott, W. H., J. L. Jackson, and J. T. Stropki, “Corrosion Prevention

and Control Final Report – Corrosion Sensor Implementation on C-130

and H-60 Aircraft,” Robins AFB Public Affairs Certification #07-0790.

[8] Lindeburg, M. R., “Mechanical Engineering Reference Manual for the

PE Exam,” Tenth Edition, Professional Publications, Inc., 1998.

[9] Abbott, W. H., “A Decade of Corrosion Monitoring in the World’s

Military Operating Environments – A Summary of Results,” Battelle

Columbus Operations, August 2008.

[10] Rees, K. S., “Corrosion in Military Rotorcraft: A Current Assessment

of U.S. Army Experience,” American Helicopter Society 58th Annual Forum,

June 11-13, 2002.

[11] “Policy Directive Governing the Execution of the Joint Airframe

Condition Evaluation (JACE) in the Field for Army and Air Force All

H-60 Aircraft,” U.S. Army TB 1-1520-237-25-2, 15 March 1997.

[12] Abbott, W. H., and S. F. Carr, “Corrosivity Sensor Applications on

Army Helicopters,” Tri-Service Corrosion Conference 2007, December 3-7,

2007.

[13] Montgomery, D. C., “Design and Analysis of Experiments,” 6th

Edition, John Wiley & Sons, Inc., 2005.

[14] Walpole, R. E., and R. H. Myers, “Probability and Statistics for

Engineers and Scientists,” Fourth Edition, MacMillan Publishing

Company, 1989.

[15] Korb, L. J., and D. L. Olson, “ASM Handbook, Volume 13:

Corrosion,” ASM International, Fifth Printing, March 1996.

[16] Pyzdek, T., “The Six Sigma Handbook, Revised and Expanded,”

McGraw-Hill Companies, Inc., 2003.

[17] Morcillo, M., E. Almeida, M. Marrocos, and B. Rosales, “Atmospheric

Corrosion of Copper in Ibero-America,” Corrosion, Vol. 57, No. 11, 2001.

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9

techsolutions 12

INTRODUCTION

In the 21st century, consumer markets demand less expensive

products that can be manufactured faster than in previous generations of a product. Therefore, advances in manufacturing concepts

and technologies must be achieved to reduce new product development times, manufacturing cycle times, and production costs. The

cost of procuring and setting up traditional production machinery

(e.g., mills, lathes, grinders, etc.) can increase the unit cost of a

product, and the impact is exaggerated if only a small number of

units are being produced. Moreover, traditional production processes are subtractive, which means that the finished product is

machined out of a larger block of material, and thus generates material waste. As the 21st century loomed on the horizon, manufacturers and product designers researched the ability of processes like

additive manufacturing (AM) to reduce machine cycle time and

waste. Additive manufacturing refers to a process that builds up a

component in layers.[1] Additive manufacturing is known by several different names, the most common of which are rapid prototyping, rapid tooling, rapid manufacturing, direct digital manufacturing, and solid free-form fabrication. This article provides an

overview of AM processes and presents current and emerging applications of AM technology for commercial and defense industries.

HISTORY OF ADDITIVE MANUFACTURING

Originally developed as a quick and cost-effective method to produce mock-up or prototype components, additive manufacturing

was first known as rapid prototyping in the mid-1980’s. Additive

manufacturing processes have since helped revolutionize the manufacturing industry and it has spun off various production technologies and tooling methods that are used throughout commercial

industry and the Department of Defense (DoD).

In 1986, Charles Hull applied for and received a patent for an

“Apparatus for Production of Three-Dimensional Objects by

Stereolithography” (US Patent 4,575,330).[5] Carl Deckard, a

researcher at the University of Texas, received a grant from the

National Science Foundation in 1987 to develop a selective laser

sintering (SLS) process.[6] Three-dimensional (3D) printing technologies developed in the 1980’s helped jump start a cottage

industry in the 21st century to produce customized components

to fill orders via the Internet. In the 1990’s, the additive manufacturing industry continued to grow as technology improved and

new concepts were developed.

With the advancement of computer-aided design (CAD) modeling technology in the 21st century, AM processes are more

capable of fabricating complex components. As a result, processes,

such as direct digital manufacturing and mass customization, have

become more practical. These advancements, in combination with

material improvements, have helped AM processes evolve from a

method for fabricating design prototypes to a method for making

fully functional prototypes, tooling, molds, and low volume production runs.

Parts fabricated via AM are traditionally produced using either

photopolymeric or metallic materials. Photopolymers are liquid,

solid, or powder-based resins that are cured and shaped using ultraviolet (UV) light sources. Metallic components, which are usually

powder-based, range from low alloy steel to aluminum, titanium,

copper, and tungsten. A more detailed list of processes and materials is provided in Table 1.

LIQUID-BASED ADDITIVE MANUFACTURING

In liquid-based AM processes a photo-sensitive polymer resin is

cured or solidified using an ultraviolet (UV) light source.[10] Such

processes are used to manufacture fully functional prototypes, mold

patterns for metal casting, and low volume production of certain

plastic components.

http://ammtiac.alionscience.com The AMMTIAC Quarterly, Volume 4, Number 2

Christopher W. Fink

AMMTIAC

Rome, NY techsolutions 12

An Overview of Additive Manufacturing, Part I

Term Definition

Rapid prototyping The use of a digital model, such as CAD, to construct a prototype by depositing

a material onto a substrate

Direct digital manufacturing Transformation of a digital representation or design of a part to a finished

product using additive manufacturing

Rapid manufacturing Use of additive manufacturing processes to make fully-functioning products

Rapid tooling The use of additive manufacturing processes to create a mold cavity or directly

fabricate a limited volume of tools

Additive

Manufacturing

Definitions

[1-4]

This article is the first part in a two-part series on additive manufacturing. It presents a brief introduction to several additive manufacturing

processes, such as stereolithography, fused deposition modeling, and laminated object manufacturing. The second installment in this two-part series

will be published in an upcoming issue of TechSolutions. - Editor

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Stereolithography

Stereolithography (SL) is used to make solid objects by successively printing thin layers of a photo-curable material.[5] To build each

layer, a pattern is drawn and cured by an ultraviolet laser whose

path is derived from a CAD drawing of the part. Once the layer is

cured, a new layer of photopolyermic resin is distributed on top of

the previous layer, and the laser curing process continues until the

part is fully formed (see Figure 1).[11] Stereolithography was also

the first AM technology developed for use in commercial applications. Originally used to produce parts for physical mock-ups in

the design phase, SL is now used for everything from short production runs to shell molds for investment casting. The high dimensional accuracy of SL produces a higher quality mold than traditional molding processes. This accuracy helps ensure the production of a more precise mold without incurring long lead times that

have plagued the investment casting process in the past.[13]

Sterolithography has made its way into the medical field in

recent years. Currently, it can be linked with image scanning

systems like computed tomography (CT) scanners and magnetic

resonance imaging (MRI) machines to produce accurate recreations of anatomical components (e.g., bones, cartilage, etc.).

These re-creations have been useful in pre-surgery planning, during which the surgical team can now more precisely identify

obstacles and plan the surgical steps prior to surgery.[14] Other

applications are listed in Table 2.

10 The AMMTIAC Quarterly, Volume 4, Number 2

techsolutions 12

Process Materials

Stereolithography Acrylic photopolymer

Epoxy photopolymer

Vinyl ether photopolymer

Fused deposition modeling Acrylonitrile butadiene styrene (ABS)

Polycarbonate

Polyester

Polyphenylsulfone

Laminated object manufacturing Aluminum

Paper

Poly vinyl carbonate (PVC)

Acrylonitrile butadiene styrene (ABS)

Polycarbonate

Polyester

Titanium nitrite

Ceramics

Miscellaneous metals

Electron beam melting* Superalloys

Stainless steels

Tool steels

Aluminum

Titanium

Copper

Process Materials

Laser Engineered Net ShapingTM* 316, 304, 17-4 stainless steels

Nickel-based superalloys

Tungsten

Copper

Aluminum

M300 steel

H13 tool steel

Titanium

Low alloy steel

Nickel aluminides

Selective laser sintering* Polystyrene

Sand

Polycarbonate

Polyamide

Glass filled polyamide

Tungsten

Copper

Aluminum

Low alloy steel

Inkjet/3D Printing* 316L stainless steel + bronze

420 stainless steel + bronze

Wax

Starch

Plaster

Molding Sand

Table 2. Industrial applications of stereolithography. [14-16]

Industry Application

Firearms Functional model for form and fit analysis

Medical Development of replica body parts for

pre-surgical planning

Fabrication of cranial implant

Surgical aid for dental implant surgery

Furniture Functional model for form, fit and function

design

Power generation Functional model for verification of redesign

Architecture Three-dimensional representation of structural

Figure 1. An illustration of the stereolithography process. (Image plans

courtesy of CustomPartNet, Copyright © 2008)[12]

Table 1. Examples of additive manufacturing processes and materials. [7-9]

Lenses

Laser

Elevator

Sweeper

Layered Part

Build Platform

X-Y Scanning Mirror

Laser Beam

Vat

Liquid

Photopolymer

* These processes will be highlighted in Part II of this article.

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SOLID-BASED ADDITIVE MANUFACTURING

Solid-based AM are processes, such as fused deposition modeling

(FDM) and laminated object manufacturing, that shape solid or

semi-solid state materials (usually through an extrusion) in a high

temperature environment. These processes are used primarily to

fabricate fully-functional prototypes and mold cavities for investment casting parts.

Fused Deposition Modeling

Invented in 1989, fused deposition modeling is a process that

produces thermoplastic and wax components through the deposition of molten material on a substrate.[17] To produce parts, the

material (usually in wire form) is heated to just below melting

temperature, extruded through a nozzle, and deposited in a

pattern developed from a CAD drawing (see Figure 2). The individual layers, which traditionally range from 0.002 to 0.030 inches, are

adhered to the previous layer through heat conduction and cooling.[19] Parts made with FDM require the use of a base, which is

a brittle material that can be easily separated from the finished

product without tools or damaging the part.[17] A base is used

because the material does not cool fast enough to maintain its

rigidity and dimensionality during deposition.

While the most common application of FDM is for the fabrication of geometric and functional prototypes, this process has

gained popularity in the casting community. Compared to injection molding, thermoplastic and wax mold cavities can be produced with greater dimensional accuracy because FDM is not as

sensitive to thermal expansion. In addition, a variety of plastic

materials and colors can be used during the production of a single

product. FDM has been used in the automotive industry for

everything from mock-up parts for racing teams to fully-functional motorcycle components.[20] A sample list of industries that use

FDM is shown in Table 3.

Laminated Object Manufacturing

Laminated object manufacturing (LOM) or laminated layer manufacturing is a process that utilizes a polyethylene coating to build

3D shapes. Developed in 1988, LOM uses rolls of a thin material

(usually paper) to build up layers in a cross-hatched pattern (see

Figure 3).[19] Each layer is heated by a roller, which activates the

adhesive backing and enables it to stick to the layer below. After

each layer is in place, the outline of a cross-sectional pattern is cut

using a carbon dioxide (CO2) laser. As the part is constructed, a

border and cubes are cut into the pattern with the laser to secure

the laminated layers during the production process.[23] Once the

part has been built up, the cubes are removed in a secondary operation. Because of the relatively simple production process, any

material that can be made into a thin foil material and cut with a

CO2 laser can be used with LOM. However, paper, plastic and

ceramic materials are the most widely used (refer to Table 1). The

LOM process has gained popularity because it can produce parts

without subjecting them to the internal stresses incurred in other

processes. Thus, LOM produced parts do not suffer distortion,

shrinkage, or material deformation because there is little internal

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AMMTIAC A D V A N C E D M A T E R I A L S , M A N U F A C T U R I N G A N D T E S T I N G

Table 3. Industrial application of fused deposition modeling.[21]

Industry Application

Automotive and racing Prototype motorcycle engine

Design prototypes for race car mock-up

Banking Production of assembly aid fixturing for

automated teller machinery (ATM)

Computer manufacturing Fully functional prototypes for computer

accessories

Fire and rescue Prototype hand-held thermal-imaging system

for fit analysis

Aviation Prototype wiring conduits for Osprey helicopter

Home and lawn care Prototype sprinklers for functional testing

Production of assembly fixtures for vacuum

cleaners

Marine Prototype parts for functional testing

Production of outer shell for whale tracking

device

Medical Prototype medical tool for functional testing

Figure 2. An illustration of the fused deposition modeling process.

(Image courtesy of CustomPartNet, Copyright © 2008)[18]

Figure 3. An illustration of the laminated object manufacturing

process. (Image courtesy of CustomPartNet, Copyright © 2008)[22]

Build Material Filament

Foam Base

Support Material Spool

Part

Part Supports

Build Material Spool

Build Platform

Support Material Filament

Extrusion Head

Drive Wheels

Liquifiers

Extrusion Nozzles

Laser

Heated Roller

Material Sheet

Platform

Material Supply Roll

Layered Part

& Support Material Waste Take-up Roll

X-Y Scanning Mirror

Current Layer

Mirror

Laser Beam

Part Layer Outline & Crosshatch

Previous Layer

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12 The AMMTIAC Quarterly, Volume 4, Number 2

tension during processing.[8] In addition, the LOM process can

produce relatively large components (up to 20x30x20 inches).[23]

LOM is primarily used in the casting and forging industries

and is capable of producing large and complex mold patterns.

This process is particularly useful in the development of molds

and dies for rapid tooling. In addition, LOM materials are traditionally non-toxic and easily disposable, which makes them ideal

for environmentally-friendly mold designs. A list of industrial

applications that utilize LOM is shown in Table 4.

SUMMARY

This article, which is part one of a two-part series on additive manufacturing, provided an introduction to several liquid- and solidbased additive manufacturing technologies. The second article in

this series will present powder-based additive manufacturing

processes, including electron beam melting, Laser Engineered Net

ShapingTM, selective laser sintering, and three dimensional printing. In addition, the article will briefly describe the benefits of

additive manufacturing for Department of Defense applications.

Further information on applications, machinery suppliers, technologies, and countries that employ additive manufacturing can be

found in the “Rapid Prototyping: State of the Art Review” published in 2003. This report can be downloaded from the following

url: http://ammtiac.alionscience.com/pdf/MT-93-01.pdf

REFERENCES

[1] “What is Direct Digital Manufacturing?”, Society of Manufacturing

Engineers, www.sme.org/ddm, accessed May 2009.

[2] Ullman, D. G., Mechanical Design Process, McGraw-Hill, 1997.

[3] Himmer, T., E. Stiles, A. Techel, and E. Beyer, “PCPro a Novel

Technology for Rapid Prototyping and Rapid Manufacturing,” 16th Solid

Freeform Fabrication Symposium, 2005, pp. 31-38.

[4] “Rapid Tooling: An Introduction,” eFunda, http://www.efunda.com/

processes/rapid_prototyping/rt.cfm, accessed May 2009.

[5] Hull, C. W., “Apparatus for Production of Three-Dimensional Objects

by Stereolithography,” UVP, Inc., Patent No. 4,575,330, 1986.

[6] “Manufacturing: The Form of Things Unknown,” America’s Investment

in the Future, National Science Foundation, 2000.

[7] Freitag, D., T. Wohlers, and T. Philippi, Rapid Prototyping: State of the

Art Review, Advanced Materials, Manufacturing, and Testing Information

Analysis Center (formerly the Manufacturing Technology Information

Analysis Center), 2003.

[8] Mueller, B., and D. Kochan, “Laminated Object Manufacturing for

Rapid Tooling and Patternmaking in Foundry Industry”, Computers in

Industry, Vol. 39, No. 1, 1999, pp. 47-53.

[9] “Applications,” Arcam AB, http://www.arcam.com/applications/

othermaterials.asp, accessed May 2009.

[10] Usher, J. M., R. Utpal, and H. Parsaei, editors, Integrated Product and

Process Development Methods, Tools, and Technologies, Wiley, 1998.

[11] “Stereolithography Prototyping Process,” Alpha Prototypes,

http://www.alphaprototypes.com/Stereolithography.aspx, April 2009.

[12] “Stereolithography,” CustomPartNet, http://www.custompartnet.

com/wu/stereolithography, accessed June 2009.

[13] Atwood, C. L., “Metal Casting Applications,” Rapid Prototyping in

Europe and Japan, JTEC/WTEC Panel Report, http://www.wtec.org/

loyola/rp/, accessed April 2009.

[14] “Advantages of Biomedical Models,” Biomedical Modeling, Inc.,

http://www.biomodel.com/advantages.html, accessed April 2009.

[15] “Rapid Prototyping Knowledgebase – Case Studies,” Stereolithography.com, accessed May 2009.

[16] “Low Volume Prototypes – Case Study,” Quickparts, http://www.

quickparts.com, accessed April 2009.

[17] Gebhardt, A., Rapid Prototyping, Hanser Gardner Publications, 2003.

[18] “Fused Deposition Modeling,” CustomPartNet, http://www.

custompartnet.com/wu/fused-deposition-modeling, accessed June, 2009.

[19] Sclater, N., and N. P. Chironis, Mechanisms and Mechanical Devices

Sourcebook, 4th Edition, McGraw-Hill, 2006.

[20] “FDM Case Study – Ducati,” Stratasys, Inc., http://www.

fortus.com/stratasys.aspx?id=409, accessed April 2009.

[21] “Success Stories,” Stratasys, Inc., http://www.fortus.com/Success_

Stories.aspx, accessed April 2009.

[22] “Laminated Object Manufacturing,” CustomPartNet, http://www.

custompartnet.com/wu/laminated-object-manufacturing, accessed June

2009.

[23] “Laminated Object Manufacturing,” Rapid Prototyping Center at

Milwaukee School of Engineering, http://www.rpc.msoe.edu/machines_

lom.php, accessed April 2009.

techsolutions 12

Table 4. Industrial applications of laminated object manufacturing. [8]

Industry Application

Plastic component fabrication Rotation molding pattern

Resin transfer molding pattern

Metallic/ceramic Sand casting pattern

component fabrication Investment casting pattern

Civil engineering Physical models

Sculpture re-creation

Medical Artificial limb patterns

Bone structures for surgical preparation

Mr. Christopher W. Fink is a Manufacturing Engineer and has been supporting AMMTIAC for two years. He received a BS in Industrial

and Systems Engineering from the Rochester Institute of Technology and is currently pursuing an MS at Syracuse University in Engineering

Management. Mr. Fink has authored or co-authored several reports and presentations.

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http://ammtiac.alionscience.com The AMMTIAC Quarterly, Volume 4, Number 2 13

BACKGROUND AND OBJECTIVE

The Department of Defense uses a variety of textile materials, both

manmade (e.g., nylon) or naturally occurring (e.g., cotton), for a variety of applications. Naturally occurring materials can be subject to

degradation by exposure to bacteria and fungi in moist environments,

while synthetic materials are susceptible to ultraviolet (UV) light.

These textile materials are typically coated with preservatives to provide biocidal and solar UV degradation protection.

One such naturally occurring material, cotton webbing, is used as

seam reinforcement in military tents in addition to numerous other

applications. To counter the deterioration of cotton webbing caused

by bacteria and fungi, it is currently coated with aqueous copper

8-quinolinolate, referred to as Copper 8. Copper 8 has been taken

off the market multiple times due to concerns from the

Environmental Protection Agency. Copper 8 is a one-component

antimicrobial agent suspension. In service, Copper 8 is supplemented by a separate water protection component that is added to the

cotton to help reduce water absorption. There is no UV protection

component added.

An off-the-shelf alternative cotton webbing treatment is RO-59-

WP (or simply RO-59), which is a three-part formulation consisting

of antimicrobial agents, water repellant, and UV protector that protects cotton fiber from microbes, moisture, and UV degradation.

RO-59 is an aqueous emulsion that chemically bonds to the fiber

and forms a protective barrier. A demonstration/validation

(Dem/Val) effort was conducted to compare the effectiveness of RO59 to Copper 8 for the treatment of cotton webbing.

EXPOSURE TESTING

Based on a recommendation from the US Army Natick Soldier

Research, Development and Engineering Center (NSRDEC) three

identical, US Army arctic tents (5-Man Arctic Tents) with cotton

webbing were procured for evaluation. Sections of webbing on each

tent received one of three different treatments: the baseline Copper

8 treatment; the baseline Copper 8 treatment with a subsequent

application of the RO-59 compound (which represented previously

coated materials that had been fielded and then subsequently treated

with RO-59); and the RO-59 treatment alone. The cotton webbing

materials were exposed to biocorrosion sources in two manners: outdoor exposure and soil exposure.

Outdoor Exposure

Complete tents were exposed to six months of weathering in various locations around North America, including Natick, MA, Fort

Lewis, WA, and St. Petersburg, FL. The exposure sites were noted

for high levels of precipitation, wide ranges of temperatures, high

relative humidity, and high levels of ultraviolet radiation, as well as

wind gusts. These conditions were judged to be relatively aggressive

towards cotton webbing and thus representative of tents deployed in

aggressive environments. Weather conditions were monitored at

each tent testing site. In addition, the tents were monitored visually and photographed.

Soil Exposure

Two different cotton webbing types were buried in composite soil*

at NSRDEC, representing the exposure of in-service tent flooring

material. One group of cotton webbing samples was coated twice

(two passes) with RO-59 at the manufacturer’s suggestion, while the

other received a single coating (one pass).

INSPECTION AND STRENGTH TESTING RESULTS

Outdoor exposed tents were visually inspected at time intervals of

two, four and six months. No significant differences between the

coated materials or the three tents were identified. It was virtually

impossible to detect any deterioration with the unaided eye. The

webbing at the ground interface seemed to survive the environments at each location with no visible degradation, but there was a

considerable amount of staining and discoloration of the tent materials in general (see Figure 1).

Tensile strength testing† was conducted at NSRDEC on webbing

extracted from the tents following the six-month exposure period.

Key results from this testing are depicted in Figure 2. Once tensile

strength testing data was obtained, a sensitivity analysis was conducted to assess confidence in the mean values measured for tensile

strength.

Additional tensile strength testing was conducted on the webbing

materials to evaluate processing parameters as well as accelerated

biodegradation under laboratory conditions. Tensile strength testing

Larry Gintert

Scott McPherson

National Defense Center for Energy and Environment

Concurrent Technologies Corporation

Johnstown, PA

Suzanne Bosselman

US Army Natick Soldier Research, Development and Engineering Center (NSRDEC)

Natick, MA

Figure 1. St. Petersburg tent ground webbing appearance.

Ground Webbing at Setup Stained Inner Lining at Six-Months

a b

http://ammtiac.alionscience.com/quarterly http://ammtiac.alionscience.com/quarterly
14 The AMMTIAC Quarterly, Volume 4, Number 2

of cotton webbing that had been buried in composite soil was

conducted by NSRDEC to assess the benefits of applying a larger

quantity of the RO-59 compound to the webbing. The testing

results indicated that there is no apparent benefit from applying

twice as much RO-59 to the cotton webbing. The tensile strength

of the “1 pass” specimens appeared to follow the same trend of

degradation as the “2 pass” specimens, leading to the conclusion

that one coating of the compound is sufficient for this application.

Figure 3 shows the results of tensile strength testing performed on

cotton webbing with three different coating combinations after

exposure to accelerated biodegradation conditions in composite soil.

Contrary to the field exposure testing, the results of this evaluation

indicate that over extended exposure the RO-59 does not retain the

same level of protection as that provided by Copper 8. Results are

comparable for up to four weeks of exposure, but then the RO-59-

treated specimens lose a considerable amount of the original strength

compared to those treated with Copper 8 and the combined treatment of Copper 8 and RO-59. This suggests that over a long exposure duration the RO-59 may not protect as well as coatings that

contain Copper 8. This finding may also support a recommendation

to reapply RO-59 after a yet-to-be determined time interval. On the

other hand, it should be noted that the harsh composite soil burial

testing conducted at NSRDEC has unknown correlation to actual

field exposure, so it is uncertain how critical the 12-week exposure

strength difference is to real-life use of the tents.

SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS

Evaluation of military tent materials was conducted in severe environmental conditions at three outdoor domestic sites. RO-59 represents a reduced environmental, health, and safety risk when compared to Copper 8 in this application. The objective was to assess

the performance of RO-59 when used alone as a tent webbing preservative, in comparison with using Copper 8 alone, and with using

RO-59 in combination with Copper 8. Additional tests were conducted in which the treated cotton webbing materials were subjected to ground burial, which is a harsher environment than above

ground exposure. In each case, the tensile strength of the exposed

samples of treated cotton webbing was subsequently determined.

Based on a statistically significant number of tent webbing test

samples, it was found that:

• In a 6-month outdoor exposure on tents, RO-59 when used

alone performed as well as Copper 8 when used alone, and as

well as RO-59 when used with Copper 8.

• When samples of cotton webbing (per MIL-W-5665) were

subjected to microbial attack, moisture and other harsh elements during ground burial tests, the measured decrease in

tensile strength was found to be similar for each of the burial

periods through 12 weeks regardless of whether the webbing

was treated with one pass of RO-59 or two passes. Thus, a

single-pass coating process should be sufficient for the candidate preservative.

• When cotton tent webbing samples (per MIL-W-530) were

subjected to ground burial tests, the measured decrease in tensile strength was found to be similar regardless of coating for a

burial period up to four weeks, but then diverged such that the

strength of the Copper 8 coated samples were superior to that

of the RO-59 coated samples after 8 weeks of burial, and even

more so after 12 weeks of burial.

As a result of these tests, the team recommended continuation of

the initiative to modify cotton webbing military specifications

through the NSRDEC and Defense Logistics Agency to include

RO-59 as an acceptable alternative to Copper 8. It was also recommended that further testing should be conducted to substantiate

whether or not reapplication of RO-59 is necessary for extended

preservation of the materials. Finally, it was recommended that the

applicability of RO-59 for cotton webbing used in other applications beyond tents be investigated by conducting testing specific to

those applications.

ACKNOWLEDGEMENTS

The authors wish to express their appreciation to the following individuals and their facility support personnel who provided assistance

with this demonstration/validation and information for this report:

Dr. Margaret Roylance, Division Leader, Materials and Defense

Sciences Division, Warfighter, Warfighter Science, Technology and

Applied Research Directorate, NSRDEC; Ms. Kris Senecal,

NSRDEC; Ms. Suzanne Bosselman, NSRDEC; Mr. John Theis,

Army Corrosion Office; Mr. Hilton Mills, Army Corrosion Program

Manager, Headquarters Army Materiel Command; Maj. Aaron C.

Bryant, Support Operations Officer, BN FTS Training Officer, St.

Petersburg, FL; Mr. Rich Gillespie, Earthworks Supervisor, Fort Lewis,

WA; Mr. Ronnie Bender, President, RO-59, Inc., Stoughton, MA;

Mr. John Mulready, Leedon Webbing Co., Inc.; Mr. Joe Fields and

Ms. Anita Braden, Outdoor Venture Corporation.

NOTES AND REFERENCES

* Test was conducted following Antifungal Activity, Assessment on Textile

Materials: Mildew and Rot Resistance of Textile Materials, American

Association of Textile Chemists and Colorists (AATCC) Test Method 30-

1999.

† American Society for Testing and Materials (ASTM) Test Method D 503,

Standard Test Method for Breaking Force and Elongation of Textile Fabrics

(Strip Method).

[1] Gintert, L., S. Scala, and S. McPherson, “Demonstration/Validation

Report for Replacement of Aqueous Copper 8-Quinolinolate Treatment of

Cotton Webbing with RO-59-WP,” National Defense Center for

Environmental Excellence, March 2008.

[2] Bosselman, S., K. Senecal, and L. Gintert, “Prevention of Material

Biodegradation – Tent Preservation Project,” US Army Corrosion Summit

2008, February 2008.

Figure 2. Mean value of tensile strength of tent webbing. Figure 3. Soil burial tensile strength results.

750

740

730

720

710

700

690

680

670

660

Tensile Strength (lbf

)

Copper 8 Copper 8 and RO-59 RO-59

St. Petersburg, FL

Natick, MA

Ft. Lewis, WA

Mean Value

for All Locations

Copper 8 Aq Copper 8 and RO-59 RO-59

900

800

700

600

500

400

300

200

100

0

Tensile Strength (lbf

)

0 Weeks

2 Weeks

4 Weeks

8 Weeks

12 Weeks

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