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AIR COMMAND AND STAFF COLLEGE

AIR UNIVERSITY

C-130 Programmed

Depot Maintenance

JOHN A. DANIELS

Major, USAF

Air Command and Staff College

Wright Flyer Paper No. 1

MAXWELL AIR FORCE BASE, ALABAMA

February 1998
Disclaimer

Opinions, conclusions, and recommendations expressed or implied within are sole

of the author and do not necessarily represent the views of Air University, the Unite

Air Force, the Department of Defense, or any other US government agency. Cle

public release: distribution unlimited.

ii
Foreword

It is my great pleasure to introduce readers to the W

Flyer Papers series. In this series, Air Command and Staf

lege recognizes and publishes the “best of the best” st

research projects from the prior academic year. The ACS

search program encourages our students to move beyon

school’s core curriculum in their own professional develop

and in “advancing air and space power.” The series title re

our desire to perpetuate the pioneering spirit embodied in 

lier generations of airmen. Projects selected for public

combine solid research, innovative thought, and lucid pres

tion in exploring war at the operational level. With this 

perspective, the Wright Flyer Papers engage an eclectic ra

doctrinal, technological, organizational, and operational 

tions. Some of these studies provide new solutions to fa

problems. Others encourage us to leave the familiar behi

pursuing new possibilities. By making these research st

available in the Wright Flyer Papers, ACSC hopes to enco

critical examination of the findings and to stimulate fu

research in these areas.

Jerry M. Drennan, Brig Gen, 

Commandant

iii

Preface

This paper examines the current USAF criteria for indu

C-130 aircraft into programmed depot maintenance (

based on the mission, design, and series (MDS) of the air

An alternative approach using an analytical model is deve

in an attempt to refine the current process. I became inter

in refining C-130 PDM intervals while serving as the C

structural engineering branch chief in the C-130 System 

gram Office (SPO). It was my observation that many C

operators and maintainers did not understand how the 

intervals had been established over the many years of C

operations.

I would like to thank Col Gregory A. Siegel, C-130 sy

program director, for sponsoring this research effort and 

his support to my interviews and correspondence with C

SPO personnel. The superb technical support of Mr. Ray

Waldbusser, C-130 aircraft structural integrity manager

invaluable in completing this research. Mr. Waldbusser 

vided critical data for this effort and provided common

answers to difficult questions. Finally, I would like to ex

my gratitude to Maj Marsha Kwolek, Air Command and 

College/War Theory and Campaign Department (ACSC/

for serving as my faculty research advisor and providing 

ance and direction during the preparation of this paper.

v

Abstract

The current USAF process for establishing C-130 PDM 

vals does not account for the wide range of aircraft var

within each aircraft MDS. This paper develops an anal

model that C-130 maintainers can use to forecast when 

130 aircraft requires PDM. The model is based on five u

aircraft variables: (1) aircraft age, (2) total flying hours, (3) 

age yearly flying hours, (4) mission profile (expressed as 

verity factor), and (5) operating location of the aircraft. 

views with C-130 SPO personnel, combined with use o

C-130 Service Life Data Base, provided the required da

developing the C-130 PDM interval model.

The C-130 PDM interval model developed in this paper a

maintainers and operators to predict the optimum tim

tween C-130 PDM activities. It eliminates the requireme

base PDM intervals on aircraft MDS. As a result, there 

potential for significant savings by deferring PDM for a po

of the C-130 fleet. Finally, the PDM interval model develop

this paper may be applicable for other Department of De

aircraft for which MDS is used as the determinant of 

intervals.

vii
C-130 Programmed Depot Maintenan

The existing procedures by which the Air Force is currently managed

have served it well, but times have changed; procedures must b

reviewed to determine which ones can be kept, which ones must b

changed, and where shortcomings suggest new procedures are re 

quired, which ones must be added.

— USAF Scientific Advisory Boar

Since the C-130 Hercules made its first flight in 1954

2,000 aircraft have rolled off the production line in Mar

Georgia. For most of these four decades, maintainers 

struggled with developing and refining procedures to mai

the C-130 fleet.

The current C-130 programmed depot maintenance 

cess is complex and is governed by numerous technica l o

and policy directives. Just as the Air Force is reengine

the sustenance of aircraft components under the “lean 

tics” banner, so the current aircraft PDM process is in 

of similar scrutiny. The over-used slogan “just-in-time” r

has as much relevance to aircraft PDM as it does to repa

line replaceable units (LRU). Inducting a C-130 aircraf

PDM typically costs close to one million dollars and take

aircraft away from the operator for 120 days. 1

 If an ai

PDM interval can be deferred one or more years, the 

savings in both money and aircraft downtime are si

cant—and this is especially true for the C-130, consid

the size of the C-130 fleet. Therefore, building an anal

model which predicts when a C-130 aircraft requires PD

a worthy endeavor.

The purpose of this paper is to provide C-130 maintain

tool they can use to predict the time between PDM activ

which is referred to as the PDM interval. A detailed discu

of the C-130 fleet and the current method used to deter

PDM intervals will provide the background necessary for 

oping the proposed C-130 PDM interval model.

The C-130 Fleet

The [C-130] Hercules genealogist soon learns that some of th

boughs of the C-130 tree are about to break with the weight of the

1
number of variants that have proliferated since the birth of mama

and papa back in Burbank [California].

— M. E. Mo

The C-130 Hercules has indeed been a workhorse fo

Department of Defense (DOD) since 23 August 1954, whe

new turboprop transport aircraft made its first flight. 2

 Th

cess of the C-130 is one reason operators around the wor

now maintaining a weapon system that is often older tha

pilots who fly it.

The USAF maintains and operates a fleet of more than 

C-130 aircraft (table 1). These aircraft are operated by six 

commands (MAJCOM), the Air National Guard (ANG), an

Air Force Reserve (AFRES). USAF C-130s are based in 56 

tions around the world. The variety of climates present

Table 1

USAF Summary of C-130 Aircraft by Operator

MDS ACC AETC AFMC AFRES AFSOC ANG PACAF USAFE 

NC-130A 1 

C-130E 106 35 4 73 8 19 

EC130E 7 8 

MC-130E 6 8 

NC-130E 1 

C-130H 40 80 146 21 

AC-130H 8 

EC-130H 14 1 

LC-130H 7 

MC-130H 3 21 

NC-130H 2 

WC-130H 10 

C-130J 2 

HC-130N 4 6 

HC-130P 9 5 7 

MC-130P 4 5 19 

AC-130U 1 12 

TOTAL 178 7 6 145 72 247 29 19 

Source: Program Management/Configuration Control and Tracking System (PM/CCAT), C-130 System 

Office, Robins AFB, Ga., 14 November 1996.
these locations results in a wide range of corrosive e

within the C-130 fleet. In addition, the fleet boasts an extr

diverse set of missions. From fighting forest fires to prov

close air support, the C-130 has proved itself a highly a

able platform. “In all, there have been more than fifty 

versions just in the U.S.”3

 As you might expect, multiple o

tors, numerous operating locations, and a wide range of 

sion profiles have greatly complicated the development of a 

size fits all” maintenance strategy for the fleet. These com

tions impact the scheduling of PDM intervals for the C

fleet.

Current Method for Determining PDM Interv

The maintenance engineering objective is to assure that the best

most timely, and most economical means, consistent with missio

requirements, are used to satisfy all approved requirements.

— USAF Technical Order (TO) 00-25-

The current PDM intervals for the C-130 fleet are presc

in TO 00-25-4, Depot Maintenance of Aerospace Vehicle

Training Equipment. The current intervals (table 2) are bas

the mission, design, and series of the C-130. Note tha

current PDM intervals vary from 48 months to 69 mo

depending on the MDS and operating location (for Pacif

Forces [PACAF] bases) of the aircraft. For example, the 

130H gunship operated by Air Force Special Operations 

mand (AFSOC) has a PDM interval of 48 months, while a 

cal” C-130H (which carries cargo and performs airdrops) 

PDM interval of 69 months.

Current PDM intervals are reviewed regularly by W

Robbins Air Logistic Center (WR-ALC) engineers, who con

numerous factors.4

 First, the MDS of the aircraft and the 

sion profiles flown by the aircraft are considered. For exa

AFSOC C-130s operate under very stressful conditions, in

ing carrying heavy payloads and often flying at low altit

many times over salt water or sand. 5 For this reason, the 

intervals for AFSOC aircraft are typically lower than tho

the rest of the C-130 fleet.

Table 2 indicates that PACAF C-130s also have a 48-m

PDM interval. This shorter interval is due to the highly c

sive environment found at PACAF installations. 6

 It is imp
to note that PDM is considered preventative maintenanc

the primary driver for C-130 PDM is corrosion. 7

Many other factors are also currently used to determine 

intervals. Product improvements, for example, and imp

materials used on newer C-130s. Also, the Aircraft Stru

Integrity Program (ASIP) is a big player in the PDM pro

ASIP provides a time-phased set of actions designed to e

the structural integrity and service life of the aircraft. 8

 A

primarily concerned with cracking in the aircraft’s stru

caused by fatigue, not corrosion. Another factor in determ

PDM intervals is the analytical condition inspection (ACI). 

are used to systematically disassemble and inspect a r

sentative sample of aircraft to find deficiencies in the ai

structure. An additional factor used to adjust PDM interv

the controlled interval inspection. These inspections look 

representative number of aircraft to decide when the PD

terval can be extended.

Table 2

Current C-130 PDM Intervals

MDS Designation PDM Interval (months)

AC-130H* 48

MC-130E* 48

PACAF C-130s 48

AC-130H 60**

WC-130H 60**

MC-130E 60***

C-130E 69**

C-130H 69***

HC-130H 60***

HC-130N 60***

HC-130P 60***

MC-130H 60 

AC-130U 60** **

* aircraft with TO 1C-130-1340 wing

** midinterval inspection at 30 months

*** 78-0806 and subsequent—initial PDM at 168 months

**** initial PDM at 144 months

Source: Scientific Advisory Board, Life Extension and Mission Enhancement for Air Force Aircraft, vol

1994.
In conjunction with the aircraft manufacturer (Lock

Martin), the C-130 SPO is also developing the aircraft corr

tracking system (ACTS). The ultimate goal of ACTS is to p

accurately where corrosion will occur.9

 In addition, the 

sion and repair recording (CARR) program is used to feed 

into ACTS. Dobbins Air Force Base (AFB), Georgia, is now 

ACTS, as is the Maryland ANG. Other units are currently 

ing their corrosion-related data to the C-130 SPO, pe

worldwide implementation of ACTS and CARR. Finally, dis

ancies found during PDM are evaluated for their effect on 

intervals.

As you can see, the C-130 SPO currently generates a 

deal of PDM-related data that affects PDM intervals. It is 

difficult, however, to integrate this data into a cohesive, u

standable PDM interval predictor.

An Alternative Approach to

Determining PDM Intervals

The real challenge is not to put a new idea into the military mind bu

to put the old one out.

— Sir Basil Liddell Har

As discussed in some detail in the preceding paragrap

lot of effort has gone into determining the current C-130 

intervals. But does the current method of establishing 

intervals produce the optimum criterion? Is there a viable 

native approach to establishing PDM intervals based o

“uniqueness” of each C-130 (even among those with the 

MDS)? The purpose of this section is to determine wheth

analytical model can be developed to facilitate “just-in-

PDM for the C-130 fleet. If we consider the analogy of main

ing an automobile, is it reasonable to assume that all P

Firebird owners should overhaul their engines and paint 

cars after a specified time interval? Probably not, so l

develop a systematic process for determining PDM interval

Primary Factors That Affect PDM Intervals

To develop a C-130 PDM interval model, we must con

the primary factors that affect PDM intervals. For simplici

us assume that the primary variables which affect the 
interval for a specific aircraft are these: (1) age, (2) flying 

total, (3) average yearly flying hours, (4) mission profile, a

operating location. Bear in mind that the variables se

here are not as important as the methodology used to de

the PDM interval model.

One advantage of developing a model is that C-130 main

ers and operators can tailor the model based on the fa

they believe to be most important. They may decide that 

factors are equally important (e.g., maintenance prac

number of landings, etc.). To further simplify this analys

will consider the C-130H model only. (There are 291 C-

aircraft.) Recall that TO 00-25-4 specifies the PDM interv

C-130H aircraft to be 69 months (except for PACAF C-

aircraft, which have a PDM interval of 48 months).

We have identified the five primary factors involved in th

tablishment of PDM intervals. They are discussed briefly her

Age. The age of an aircraft can reasonably be expect

affect PDM intervals; that is, the older an aircraft, the 

likely the aircraft is to experience corrosion damage. The 

Scientific Advisory Board noted that “intervals between 

grammed depot maintenance are increasing, which is inco

tent with maintenance requirements for aging aircraft.” 

craft age may be a significant factor affecting PDM interva

older C-130s, some of which are well over 30 years old. 

data from the C-130 Service Life Data Base is examined f

C-130H fleet, the range in aircraft age is significant (table 3

Total Flying Hours. The total number of hours an ai

has flown may reasonably be expected to affect the PDM 

val. Flying hour totals on an airframe contribute to fa

which can cause cracking and can reasonably be expect

affect corrosion since the aircraft is exposed to moisture d

Table 3

C-130H Fleet Aircraft Age

Oldest Aircraft 364 months

Newest Aircraft 7 months

Average Aircraft Age 120 months

Source: C-130 System Program Office, C-130 Life Data Base, 2 January 1997.
almost all flight operations. Table 4 shows the wide ran

total flying hours for the C-130H fleet.

Hours Flown Per Year. The number of hours flown pe

may affect the PDM interval for reasons similar to those 

tioned in the preceding paragraph. Aircraft which fly mor

quently than other aircraft may require more frequent 

intervals. Obviously, this factor is also related to total 

hours. Table 5 depicts data for the C-130H fleet in term

flying hours per year.

Mission Profile. The mission flown by each aircraft w

fect its PDM interval. For every USAF C-130, the SPO 

calculated its “severity factor.” This factor is used to qu

the airframe stresses experienced by the aircraft. This d

critical to the USAF ASIP. “The severity factor is an indicat

how the mission profile has affected the crack growth ra

the center wing lower surface panels . . . in general, the h

the severity factor, the more severely the aircraft has been 

(e.g., more high-speed, low-level flight at higher gross weig

Each C-130 aircraft is assigned a severity factor (table 6

tracked in the C-130 Service Life Data Base, which is 

tained by the ASIP manager in the C-130 SPO. These se

Table 4

C-130H Fleet Aircraft Total Flying Hours

High Aircraft Time 15,600 hours

Low Aircraft Time 20 hours

Average Aircraft Time 5,200 hours

Source: C-130 System Program Office, C-130 Life Data Base, 2 January 1997.

Table 5

C-130H Fleet Flying Hours per Year

High Yearly Hours 687 hours

Low Yearly Hours 268 hours

Average Yearly Hours 482 hours

Source: C-130 System Program Office, C-130 Life Data Base, 2 January 1997.
factors are calculated from service life data documente

AFTO Form 151A and provided by the operating loca

These forms are updated monthly. It is important to note 

an aircraft with a severity factor twice that of another ai

“has a center wing lower surface crack growth rate twice t

the aircraft with the lesser severity factor.” 12

Operating Location. Finally, the operating location 

affect the PDM interval. An aircraft based at Davis Mon

in Arizona would not be expected to experience the same 

of corrosion as an aircraft based in Japan or Hawaii. Ac

ing to the USAF Scientific Advisory Board, “corrosion i

of the most expensive maintenance issues for th

Force.”13 Corrosion severity factors have been establishe

most USAF operating locations. The higher the corrosio

verity factor, the more likely that corrosion will occur. T

factors vary widely, depending upon the geographic loc

of the base (e.g., proximity to salt water) and other env

mental factors (e.g., industrial “fallout” from factories). 

7 depicts the corrosion factors for most of the C-130H op

ing locations. Recall that the PDM interval for PACAF C-

aircraft is 48 months, while the interval for other C-

aircraft is 69 months; the difference is due to corrosion. 

ever, a close look at table 7 indicates several other C-

operating locations have the same high corrosion fac

“25” found at Elmendorf AFB, Alaska (PACAF). When w

amine the data, summarized in tables 3 through 7, 

apparent that there is a wide range of variables affecting 

intervals for the C-130H fleet. Given this wide range of 

ables, it may be beneficial to account for the variations 

develop our PDM interval model based on specific ai

(“just-in-time”) PDM rather than on MDS.

Table 6

C-130H Fleet Mission Lifetime Severity Factor

High Severity Factor 7.68

Low Severity Factor .09

Average Severity Factor 1.94

Source: C-130 System Program Office, C-130 Life Data Base, 2 January 1997.
Table 7

Summary of C-130H Bases, Corrosion Factors, and MAJCO

Location Corrosion Factor MAJCOM

Baltimore 5 ANG

Channel Islands 25 ANG

Charleston 10 ANG

Charlotte * ANG

Cheyenne 5 ANG

Dallas 10 ANG

Davis Monthan 5 ACC

Dobbins 10 AFRES

Duke Field 25 AFRES

Dyess 5 ACC

Edwards 10 AFMC

Eglin 25 AFMC

Elmendorf 25 PACAF

Harrisburg * ANG

Hickam 25 ANG

Hurlburt 25 AFSOC

Kadena 25 AFSOC

Keesler 25 AFRES

Kirtland 10 AETC

Kulis 25 ANG

Little Rock 10 ACC/ANG

Louisville 10 ANG

Mansfield 5 ANG

Martinsburg 5 ANG

Maxwell 10 AFRES

McEntire 10 ANG

Mildenhall * AFSOC

Minneapolis 5 AFRES

Mitchell 5 AFRES

Moffett 25 ANG

Moody 10 ACC

Nashville 20 ANG

New Orleans 25 ANG

Niagara 5 AFRES

Ontario 20 AFMC

Patrick 25 ACC/AFRES

Peoria * ANG

Peterson 10 AFRES

Pittsburgh 10 AFRES

Pope 10 ACC

Portland 10 AFRES

Quonset 25 ANG

*data was not available for these bases
PDM Interval Model Development

I propose that a simple relationship exists between the 

interval and the five factors discussed above, and tha

relationship can be expressed as:

Equation #1

PDM Interval = [F1(wt1) + F2(wt2) + F3(wt3) + F4(wt4) + F5(wt5)]

Where:

F1 is aircraft age factor; wt1 is importance of F1 to PDM interval

F2 is flying hour total; wt2 is importance of F2 to PDM interval

F3 is average yearly flying hours; wt3 is importance of F3 to

 PDM interval

F4 is aircraft lifetime severity factor; wt4 is importance of F4 to

 PDM interval

F5 is corrosion factor of operating location; wt5 is importance of

 F5 to PDM interval

A close look at equation #1 and the data shown in tab

through 7 indicates that the data for the five factor

through F5) must be normalized to make any sense. It w

not make sense to plug 15,600 flight hours (table 4) into 

tion #1 when we might use a very small number for the se

factor. If we did not normalize the data, the large numbers 

Table 7 (cont’d)

Summary of C-130H Bases, Corrosion Factors, and MAJCO

Location Corrosion Factor MAJCOM

Ramstein * USAFE

Reno 10 ANG

Rockwell 10 AFMC

Savannah 25 ANG

Schenectady 10 ANG

Selfridge 5 ANG

St. Joseph 10 ANG

St. Paul * ANG

Suffolk 5 ANG

Will Rogers 5 ANG

Willow Grove 10 AFRES

Wilmington 10 ANG

Yokoto 10 PACAF

Youngstown 10 AFRES

*data was not available for these bases

Source: C-130 System Program Office, 15 January 1977. Correspondence with Aircraft Structural Integri

(ASIP) Manager, WR-ALC/LBR.
total flight hours) would dominate our calculations and sm

numbers (e.g., severity factors and corrosion factors, w

may be critical to the PDM interval) would not affect the c

lated PDM interval. Therefore, the data (F1 through F5) i

C-130 Service Life Data Base must be normalized for eac

craft in the C-130 inventory; this is a simple task. For exa

the aircraft having the greatest number of total flying hour

15,600 such hours (table 4). If we want to assign a nu

between 1 and 5 to represent total aircraft flying hours (F2

simply “band” the data as follows:

F2 = 1 (for aircraft between 0 and 3,120 total flight hours)

F2 = 2 (for aircraft between 3,120 and 6,240 total flight hours)

F2 = 3 (for aircraft between 6,240 and 9,360 total flight hours)

F2 = 4 (for aircraft between 9,360 and 12,480 total flight hours)

F2 = 5 (for aircraft between 12,480 and 15,600 total flight hours)

Following the same procedure (banding) for the variable

F3, F4, and F5, tables 1, 3, 4, and 5 yield the following valu

F1 = 1 (for aircraft between 0 and 73 months old)

F1 = 2 (for aircraft between 73 and 146 months old)

F1 = 3 (for aircraft between 146 and 218 months old)

F1 = 4 (for aircraft between 218 and 291 months old)

F1 = 5 (for aircraft between 291 and 364 months old)

F3 = 1 (for aircraft between 0 and 137 average flying hours per year)

F3 = 2 (for aircraft between 137 and 275 average flying hours per year

F3 = 3 (for aircraft between 275 and 412 average flying hours per year

F3 = 4 (for aircraft between 412 and 550 average flying hours per year

F3 = 5 (for aircraft between 550 and 687 average flying hours per year

F4 = 1 (for aircraft between 0 and 1.54 lifetime severity factor)

F4 = 2 (for aircraft between 1.54 and 3.07 lifetime severity factor)

F4 = 3 (for aircraft between 3.07 and 4.61 lifetime severity factor)

F4 = 4 (for aircraft between 4.61 and 6.14 lifetime severity factor)

F4 = 5 (for aircraft between 6.14 and 7.68 lifetime severity factor)

F5 = 1 (for aircraft between 0 and 5 corrosion factor)

F5 = 2 (for aircraft between 5 and 10 corrosion factor)

F5 = 3 (for aircraft between 10 and 15 corrosion factor)

F5 = 4 (for aircraft between 15 and 20 corrosion factor)

F5 = 5 (for aircraft between 20 and 25 corrosion factor)
The only other concern is to determine wt1 through w

equation #1. Here is where the PDM interval model de

strates its flexibility. C-130 maintainers may decide that c

sion based on operating location has twice the impact on 

intervals than does the average number of flying hour

year. If this is the case, then wt5 would be assigned a 

twice that of wt3. For simplicity, I will assign the foll

values for wt1 through wt5:

wt1 = 1 (for importance of aircraft age in affecting the PDM interval)

wt2 = 1 (for importance of total aircraft flying hours in affecting the

 PDM interval)

wt3 = 1 (for importance of average yearly flying hours in affecting

 the PDM interval)

wt4 = 2 (for importance of lifetime severity factor in affecting the

 PDM interval)

wt5 = 2 (for importance of operating location in affecting the

 PDM interval)

Thus, it is assumed that aircraft usage (severity factor

aircraft operating location (corrosion factor) are twice as c

as the other three variables (aircraft age, total flying hours

average number of hours flown per year). Using the analog

car, the manner in which it is driven and the environme

which it is operated may be more important than its ag

total accumulated mileage, and its annual mileage.

Applying the PDM Interval Model

One obvious advantage of the PDM interval model is th

the data needed to calculate the PDM intervals already exi

the C-130 SPO. Additional data does not have to be obt

from C-130 operating locations. Equation #1 may be 

applied to the C-130H portion (291 aircraft) of the C-13

vice Life Data Base. The PDM interval expressed in equati

now becomes a measurable (and an explainable) indica

when a specific C-130H aircraft requires PDM. Bear in 

that the PDM interval expressed in equation #1 is no

pressed in months—it is an indicator (relative to other C-

aircraft) of the predicted combination of effects on the 

interval due to aircraft age, flying hour total, average y

flying hours, mission profile (stated in terms of severity fa

and operating location of the aircraft. Let us take a closer 
at the data resulting from our calculations (fig. 1). Note th

“nondimensional” PDM interval (as calculated from equ

#1) ranged from a low of 9.00 to a high of 28.00. In add

there were large numbers of aircraft between the low of 

and the high of 28.00.

Keep in mind that the higher the nondimensional PDM 

val, the more likely the aircraft is to require a shorter 

interval (in terms of months). At first glance, this would ind

(based on our assumptions so far) that for the entire C-

fleet, a fixed PDM interval may not be the best practice. A

considerable interest is that the four highest nondimens

PDM intervals (25, 26, 27, and 28) depicted in figure 1 

calculated for PACAF aircraft at Elmendorf AFB. This 

some support to the lower PDM interval (48 months) spe

by TO 00-25-4 for PACAF C-130H aircraft. To complet

analysis, we must correlate the nondimensional PDM in

depicted in figure 1 with time (in months).

Figure 1. Number of C-130H Aircraft versus “Nondimens

PDM Interval
Defining the Nondimensional

PDM Interval in Time

Assuming that the 48-month PDM interval for PACA

130H aircraft prescribed in TO 00-25-4 is a “good” nu

established over many years of maintenance experience, w

correlate our highest nondimensional PDM interval (28.0

fig. 1) with 48 months. In addition, assuming that the 

month initial PDM for new C-130H aircraft prescribed 

00-25-4 is a good number, we can correlate our lowest n

mensional PDM interval (9.00, see fig. 1) with 168 month

establishing this relationship, we can construct the st

line shown in figure 2. Note that figure 2 assumes a 

relationship between the upper and lower PDM interval

though this linear assumption may not be totally preci

allows for model simplification. Verifying the validity o

linear assumption by using PDM maintenance findings w

discussed later. The upper and lower bounds of the PDM 

val specified in TO 00-25-4 have not changed (168 month

48 months respectively). It is now possible to stratify a

C-130H aircraft between these upper and lower bounds. 

correlating the 69-month PDM interval (specified by TO 00

with our nondimensional PDM interval indicates that th

month PDM interval may be conservative (see fig. 2; not

number of aircraft above the 69-month interval line). Ther

the PDM interval model developed here indicates that an 

val based on the MDS of the aircraft may not be the opti

criterion.

Figure 3 depicts proposed PDM intervals for the C-130H 

based on the PDM interval model. It is important to note 

our model predicts the PDM interval by individual aircraft 

number, not by aircraft MDS.

The PDM interval model predicts a 168-month PDM in

for only two of the C-130H aircraft. A glance at the suppo

data (appendix) indicates that these two aircraft are serial 

bers 9406705 and 9203284. Thus, the spreadsheet in th

pendix can be used to predict the PDM interval for ea

130H aircraft in the USAF fleet. This capability is cr

because C-130 operators must forecast their PDM requirem

to accurately predict funding for future years.
Figure 2. “Nondimensional” PDM Inteval versus Time (in mo

Figure 3. Proposed PDM Intervals (in months) versus Num

C-130H Aircraft)
Managed Risk versus Risk Avoidance

The PDM model demonstrated above indicates that PD

tervals for the C-130 fleet can be determined using an an

cal model. But how do we know whether the model w

First, data must be analyzed for each aircraft undergoing 

This data should be analyzed by SPO engineers to refin

PDM interval model. For example, PDM data may indicate 

the corrosion factor impacts the PDM interval even more 

the weighted factor used in the PDM interval model. If t

the case, the value for “wt5” should be increased and the 

bers for PDM intervals should be recalculated. In addition, 

data and data from operational units should be used to 

the PDM interval model by adjusting the other factors us

the model. Continuous feedback is required to manage th

associated with refining PDM intervals. The information re

tion has made a PDM interval model both feasible and rela

simple. It allows us to go beyond the conservative (risk a

ance) approach, which predicts PDM intervals based on ai

MDS. Figure 4 depicts the PDM interval model graphically.

The PDM and operational data depicted in figure 4 also 

it possible to consider expanding the upper limit of the cu

PDM interval (168 months). Again, this change should be 

only if the data from PDM and ACTS indicate that this in

can be extended safely.

Advantages of the PDM Interval Model

There are many advantages to be gained in adoptin

PDM interval model. The model is flexible and allows tai

based on maintenance findings; it is applicable to the 

C-130 fleet and may have application to other USAF (and 

aircraft currently using MDS as the PDM interval determi

and it has the potential for huge cost savings through defe

PDM activities. In addition, data required for the PDM in

model is already being collected. The model also has the p

tial to improve C-130 fleet management by providing ad

indications that certain aircraft are likely to experience inc

ing maintenance requirements. (These aircraft may be reti

transferred to less severe operating locations.) In addition

and AFRES bases that operate C-130s purchased in the 

year now have a model that allows them to predict whi
their aircraft will require PDM first and to see exactly how 

intervals are determined/adjusted for their aircraft. Fi

PDM intervals are still predicted in advance to allow oper

time to schedule aircraft downtime and project budgets to 

PDM costs.

Summary

The DoD must recognize the critical importance of widely applyin

advanced information technology . . . this is the direction in which

world-class commercial firms are moving, and the DoD must be par

of that transformation.

— Defense Conversio

Over the past four decades, the C-130 community has d

superb job in maintaining an invaluable asset for the U

However, with the advent of the information revolution

maintenance community is overdue in taking the next l

step of implementing “just-in-time” PDM for the entire C

fleet. Predicting the PDM intervals for specific aircraft 

logical alternative to predicting PDM intervals based on ai

MDS. A wide range of aircraft variables exists within each 

These variables should be taken into account, and the 

interval model makes this possible.

Figure 4. Proposed PDM Interval Model
Recommendations for Senior USAF Leader

• Consider implementing the PDM interval model fo

C-130 fleet. In addition, consider applying the PDM 

val model for other USAF aircraft which also base 

intervals on MDS. Implementation could be accomp

in steps; for example, the PDM interval model cou

refined by SPO engineers and used for a portion of the 

as a pilot program.

• Charter a team to calculate the cost savings assoc

with implementing the PDM interval model. In my op

they will be substantial.

• Charter a team to integrate the PDM interval model 

other existing systems (ACTS, ASIP, PDM discrepa

etc.). Supporting data systems should provide linked 

bilities with common format. In this area, civilian co

nies with linked data systems expertise should be 

sulted for assistance.

• Sponsor research on the ability of the PDM interval m

to predict PDM actions (in addition to intervals). The 

should not only implement “just-in-time PDM,” but s

also have “tailored PDM” based on predicted mainten

actions. This research could significantly benefit th

craft Repair Enhancement Program (AREP), which 

tempting to reduce the number of days an aircraft sp

in PDM.

Notes

1. Raymond Waldbusser, Aircraft Structural Integrity Manager, C-13

tem Program Office, WR-ALC/LBR, interviewed by author, 16 October 19

2. Lindsay Peacock, Mighty Hercules: The First Four Decades (London

Air Force Benevolent Fund Enterprises, 1994).

3. Ibid., 1.

4. Capt Dee J. Jackson and Capt Edward R . Kramer, Letter Report Re

Air Force Depot Induction Frequencies (Maxwell AFB, Gunter Annex, A

Force Logistics Management Agency, June 1994); Aircraft Structural In

Manager interview.

5. Life Extension and Mission Enhancement for Air Force Aircraft, 

Panel Reports (Washington, D.C.: USAF Scientific Advisory Board, 

1994).

6. Ibid., 3.

7. Ibid.

8. Ibid., 1.

9. Ibid., 3.
10. Life Extension and Mission Enhancement for Air Force Aircraft, 

Executive Summary (Washington, D.C.: USAF Scientific Advisory Board, 

1994).

11. C-130 System Program Office, to Aircraft Structural Integrity P

Manager, WR-ALC/LBR, letter, 2 January 1997.

12. Ibid.

13. Ibid., 1.
Appendix

Modified C-130 Service Life Data Bas

The C-130H portion of the C-130 Service Life Data Bas

cel format) was modified to support the calculations requir

the C-130 PDM interval model. The first 10 rows from this 

base are shown in table 8. The data base was sorted b

PDM interval (last column), and aircraft entries (each ro

picts data on a specific aircraft) are listed by descending 

intervals as predicted by the PDM interval model.

Due to the large size of the modified C-130 Service Life 

Base, the entire spreadsheet was not “pasted” into this 

ment. Each row in the spreadsheet contains information 

specific C-130 aircraft. For those individuals interested i

veloping a similar spreadsheet, the following information i

vided.

Column #1 (“A/C Serial #”): Aircraft serial number c

directly from C-130 Service Life Data Base.

Column #2 (“Flying Hrs”): Total flying hours comes di

from C-130 Service Life Data Base.

Column #3 (“Base”): This is the operating location o

specific aircraft listed in each row. Operating location c

directly from C-130 Service Life Data Base.

Column #4 (“Lifetime Sev Fac”): This is the lifetime se

factor that represents the cumulative mission profiles th

craft has been exposed to (i.e., how the aircraft has been u

This data comes directly from C-130 Service Life Data Base

Column #5 (“Flying Hrs per Yr”): This is the average nu

of hours the aircraft has flown per year (averaged over th

two years). This data comes directly from C-130 Servic

Data Base.

Column #6 (“A/C Age [Mes]”): This is the aircraft a

months. This data comes directly from C-130 Service Life 

Base.

Column #7 (“Corr Fac”): This is the corrosion factor e

lished for the operating location of the aircraft (i.e., the b

See Table 7 for data.

Column #8 (“F1”): This number represents the norm

value for aircraft age.

Column #9 (“F2”): This number represents the norm

value for total flying hours.

23
24
Column #10 (“F3”): This number represents the norm

value for average flying hours per year.

Column #11 (“F4”): This number represents the norm

value for the lifetime severity factor.

Column #12 (“F5”): This number represents the norm

value for the corrosion factor of the specific operating locat

Column #13 (“PDM Interval”): This number represent

“nondimensional” value calculated for the recommended 

interval.

Column #14 (“PDM [months]”): This number represent

recommended PDM interval in months.

25
Bibliography

C-130 System Program Office. C-130 Service Life Data Ba

January 1997.

———. Program Management/Configuration Control and Tra

System. Robins AFB, Ga., 14 November 1996.

C-130 System Program Office. To Aircraft Structural Int

Program (ASIP) Manager, WR-ALC/LBR. Letter. 2 Ja

1997.

———. Letter. To Aircraft Structural Integrity Program 

Manager, WR-ALC/LBR, 15 January 1997.

Gansler, J. S. Defense Conversion. Cambridge, Mass.

Press, 1996.

Interview. Aircraft Structural Integrity Program (ASIP) Man

C-130 System Program Office, WR-ALC/LBR, 16 Oc

1996.

Jackson, Capt Dee J., and Capt Edward R. Kramer. Lett

port Review of Air Force Depot Induction Frequencies. 

well AFB, Gunter Annex, Ala.: Air Force Logistics Ma

ment Agency, June 1994.

Morris, M. E. C-130: The Hercules. Novato, Calif.: Pr

Press, 1989.

Peacock, Lindsay. Mighty Hercules: The First Four Dec

London: Royal Air Force Benevolent Fund Enterp

1994.

USAF Scientific Advisory Board. Life Extension and Missio

hancement for Air Force Aircraft, vol. 1, Executive 

mary. Washington, D.C., August 1994.

———. Life Extension and Mission Enhancement for Air 

Aircraft, vol.2, Panel Reports. Washington, D.C., A

1994.

USAF Technical Order (TO) 00-25-4, Depot Maintenance of 

space Vehicles and Training Equipment, June 1995.

27