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Examines patterns in commercial aircraft maintenance costs as aircraft grow older to produce lessons about aging aircraft that may be relevant to the Air Force.
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Examines patterns in commercial aircraft maintenance costs as aircraft grow older to produce lessons about aging aircraft that may be relevant to the Air Force.
The United States Air Force is interested in estimating how maintenance costs associated with its various aircraft will change over time. The Air Force is also interested in how maintenance costs might evolve for new aircraft not yet in its inventory. Future maintenance cost projections are important for budgeting purposes, but they are also central to optimal aircraft replacement calculations of the sort done by Greenfield and Persselin (2002) and Keating and Dixon (2003). If an existing aircraft's maintenance costs grow more quickly, its optimal replacement date will move forward. Conversely, if a replacement aircraft is projected to have rapidly escalating maintenance costs, the Air Force may wish to hold on to an existing aircraft longer.
Pyles (2003) is a fairly recent, and quite exhaustive, analysis of "age effects" (i.e., how maintenance costs change as aircraft grow older) in military aircraft. (The literature review in Chapter Two has further discussion of the Pyles study and other analyses of military aircraft.) This report complements the literature on aging military aircraft by focusing instead on commercial aviation.
There are, obviously, important differences between commercial and military aviation. Commercial aircraft are operated many more hours per day-a commercial aircraft might have tentimes as many lifetime flying hours as a military aircraft of similar age.
Perhaps as a result of fewer flight hours per year, the Air Force is currently operating some aircraft (e.g., the B-52, the KC-135) at ages not seen in U.S. commercial aviation. As discussed in Chapter Three, commercial aircraft are generally disposed of by U.S. airlines by around age 25. Hence, the analysis in this document is not informative as to what might happen to maintenance costs of the Air Force's oldest aircraft.
Of course, commercial aviation is not intended to operate in the hostile conditions of combat. For instance, damage from anti-aircraft weapons or super-normal gravitational forces should not be observed in commercial aviation.
Why, then, might commercial aviation be of interest to the Air Force? There are several possible motivators for analyzing commercial aircraft costs in order to gain insights on military aircraft maintenance costs, although the reader must ultimately decide on the relevance of this study.
First, the Air Force owns and/or is considering purchasing aircraft that have commercial analogs. The Air Force's executive transport aircraft are essentially commercial-off-the-shelf (COTS) except with military communications (e.g., identification, friend or foe) equipment installed. More importantly, the Air Force's cargo and tanker aircraft are similar to commercial passenger aircraft. The Air Force, for instance, is currently considering acquiring a tanker variant of an existing Airbus and/or Boeing commercial passenger airliner. While such a commercially derived tanker would not be equivalent to its passenger cousin, it is reasonable to think its maintenance issues could be analogous.
Second, the RAND study team hypothesized that some commercial aviation aging effects may be similar to those of the Air Force, notwithstanding major differences in usage. At the risk of gross oversimplification, there are two basic causes of maintenance costs. The more intuitive cause is usage: Every time an aircraft takes off or lands or flies for an hour, a certain amount of wear and tear occurs that requires maintenance. The less intuitive cause of maintenance is time itself: Destructive processes, such as corrosion or seals drying out, occur irrespective of whether an aircraft is flying. Commercial experience is especially relevant to the Air Force to the extent that calendar-age-related maintenance costs are important.
Third, commercial aviation maintenance cost data have been collected that may prove to be more comprehensive and more detailed than military maintenance cost data. Pyles (2003), for instance, observed that
the Air Force has no comprehensive system for historical maintenance and material consumption data. Some historical data exist only as hard-copy records kept in office file cabinets or in old reports archived sporadically.
Chapter Three discusses the commercial aviation data gathered by the Department of Transportation (DoT) that were used in this study. Although all data sets have shortcomings, these DoT data provide a 1965-2003 annual time series that goes far beyond the duration of most military maintenance data sets.
The remainder of this monograph is organized as follows: Chapter Two presents a literature review on aging aircraft. Chapter Three commences with a simplified overview of how commercial aircraft are maintained and then discusses the DoT commercial aviation maintenance data on which this document is based. Chapter Four presents the results of the analysis. It presents estimates of how commercial aircraft maintenance costs typically change as commercial aircraft grow older. Chapter Five discusses a prospective bias in the estimation. Specifically, the concern is that commercial airlines might be prematurely retiring "poorly aging" fleets-an option probably not available to the Air Force. Fortunately, evidence of such an effect was not found. Chapter Six provides the conclusions, and a technical appendix provides detailed results of the estimations.
This chapter discusses the literature and prior research relating to aging-aircraft issues. While research undertaken in the 1960s did not consistently find maintenance costs increasing as aircraft aged, more recent studies have generally found an aging effect. Table 2.1 summarizes previous studies in chronological order. The "age effect" column has a "+" in it if the study found a positive age effect-i.e., real (inflation-adjusted) maintenance costs grew as aircraft aged. The studies looked at multiple models and explanatory variables. Some combinations yielded no age effect, while others did. A "No" in the age effect column indicates that there was no age effect worth reporting in the analysis. None of the authors of these studies reported negative age effects. The next section covers each of the studies individually.
Chronology of Prior Studies
Since the advent of aviation maintenance, those responsible for maintaining aircraft have been concerned not only with the current cost of maintenance but also the future cost. The Air Force is no exception. Studies going back to the 1960s demonstrate the Air Force's historical concern over the expected future cost of its fleet maintenance.
Kamins (1970) Found Lack of Age Effect
In a RAND study published in 1970, Kamins cited ten different analyses that attempt to illustrate the effect of age on maintenance cost. He briefly critiqued three studies that show a positive age effect but argued that the studies are insufficient, primarily because the data were cross-sectional, the data points were few, and the representation of aircraft of various ages was skewed and over-represented by older aircraft. In the early studies, the two aircraft of interest were the B-52 and the KC-135A.
Kamins then moved to seven studies he said prove that there is no age effect. In fact, some of the studies seemed to demonstrate that aircraft actually become more reliable as they age. One study used accidents as the dependent variable, with the argument that accident rates decreased as aircraft got older, thus demonstrating a negative age effect. A second study summarized findings from United Airlines and Pan American Airlines that stated that due to process improvements in maintenance, maintenance requirements actually decreased as aircraft aged.
The studies that were used to justify the lack of age effect have a small number of observations. Extrapolations of any results were nearly impossible. These studies were completed while aviation was still in its youth and when aircraft were retired because of technological advances and not because of maintenance costs.
Kamins demonstrated that aging aircraft are not unique to the military. The airlines and aircraft manufacturers are equally, if not more, concerned than the Air Force with growth in the cost of maintenance. However, most of the available literature regarding age effects focuses on military fleets.
Hildebrandt and Sze (1990) Found Positive Age Effects
Hildebrandt and Sze (1990) developed several O&S cost-estimating relationships in which models were estimated to determine the effect of specified explanatory variables on different aggregations of O&S cost. Aircraft mission design age was included in their analysis as one of the explanatory variables. They emphasized the explanatory power of a total O&S cost model in which flyaway cost is a proxy for both aircraft mission type and the year an aircraft entered the inventory. They also examined specifications that attenuated the fact that flying hours are used, in many cases, to allocate costs to an aircraft mission design series. For a depot maintenance model, they estimated an aging effect of about 2.0 percent per year of aircraft design age. For the aircraft overhaul subcategory, they found that a one-year increase in aircraft mission design age increases costs by about 3.1 percent.
While Hildebrandt and Sze estimated the allocation of the funds to specific maintenance costs, the commercial data used in their report contain the actual dollars spent annually on labor, materials, and overhead for maintenance for a specific fleet.
Johnson (1993) and Stoll and Davis (1993) Found Evidence of Larger Age Effects
The Naval Aviation and Maintenance Office (Johnson, 1993) found significant age effects on total maintenance workloads in naval aircraft over a 13-year period. Also in 1993, Stoll and Davis found smaller naval aircraft age effects in on-equipment workloads over approximately the same period of time.
Ramsey, French, and Sperry (1998) Used Commercial Data to Estimate KC-135 Age Effects
The Oklahoma City Air Logistics Center led a KC-135 Cost of Ownership Integrated Product Team (IPT) study (Ramsey, French, and Sperry, 1998). The purpose of the study was to develop aging-aircraft maintenance cost trends for the KC-135 based on a review of historical commercial and military data. Ramsey, French, and Sperry used military data from the Air Force combined with 12 years of commercial panel data from the DoT. They used aircraft types similar in structure, size, and composition to the KC-135. They reported varying annual airframe maintenance cost growth rates for various commercial aircraft, e.g., 3.5 percent for DC-9s, 9 percent for DC-10s.
Francis and Shaw (2000) and Jondrow et al. (2002) Demonstrated Positive Age Effects for Navy Aircraft
The Center for Naval Analyses analyzed the Navy's F/A-18 Hornets. Francis and Shaw (2000) of the CNA used two different datasets to gain information about F/A-18 maintenance costs. Both datasets have information on the individual tail numbers. The first dataset contains ten years (1990-1999) worth of data about the usage and maintenance of every tail number of the F/A-18s in inventory. This information includes aircraft age, squadron manning numbers, maintenance time, deployment status, flight hours, and sorties. Their regression model used the log of maintenance man-hours as the dependent variable and several independent variables including number of flight hours, deployment status (e.g., whether the aircraft was deployed during the month in question), personnel variables, and age. They found a significant age effect. The age effect was 6.5 percent to 8.9 percent per calendar year of age. Additionally, they found that the flight hours and deployment status were significant indicators of the man-hours required for maintenance.
The second dataset contained information about every F/A-18 sortie flown in one month along with records of the surrounding maintenance activities. Francis and Shaw employed a probit model to estimate the probability that an F/A-18 would require unscheduled maintenance after a sortie. The independent variables were aircraft age, length of time since last depot-level maintenance, and an indicator for whether the sortie was carrier-based. They estimated that a one-year gain in age significantly increased (by 0.8 percent) the probability of unscheduled maintenance and a carrier-based sortie significantly increased (by 3.5 percent) the probability of needing unscheduled maintenance.
Another CNA study (Jondrow et al., 2002) found age effects for all types of Navy aircraft. Jondrow et al. used a log-linear model with parameters estimated with weighted least squares. The independent variables used were the annual hours flown, the percentage change in average age of a Type Model Series (TMS) (e.g., F-14A), and a categorization of the type of aircraft (carrier-based fixed wing, land-based fixed wing, or rotary wing). The dependent variable is the number of repairs per flight hour. Jondrow et al.'s goal was to help the Navy understand the effective cost of a new aircraft so that the Navy can make informed repair-versus-replace decisions. At the mean aircraft age in the dataset, they found repair-per-flight-hour age effects of 1.9 percent, 1.7 percent, and 7.9 percent for the land-based aircraft, rotary-wing aircraft, and carrier-based aircraft, respectively.
Jondrow et al. also found that some aircraft become significantly less expensive to maintain as they near retirement (the end of their service life). Readiness (the aircraft mission-capable rate) generally declines as aircraft age, but they found that as the F-14 and A-6 neared retirement, their readiness increased. Selective decommissioning is a cited reason for increased readiness near retirement. Another cited reason is that spare parts and maintainers do not drop proportional to the number of aircraft retired (Jondrow et al., 2002, slide 31).
Kiley (2001) Found Lower Aircraft Age Effects
In a Congressional Budget Office study, Kiley (2001) examined the age effects on all military equipment, including aircraft. The purpose of the study was to understand the rise in the military's O&S expenditures and discuss prior literature about the effects of age on O&S expenditures, which includes maintenance. Kiley did no new analysis with raw data. However, as stated in the report, "Those studies typically found that the costs of operating and maintaining aircraft increase by 1 to 3 percent with every additional year of age after adjusting for inflation" (Kiley, 2001).
Pyles (2003) Found Specific Age Effects on Workloads and Material Consumption
Pyles (2003) is the most comprehensive study of age effects on Air Force aircraft to date. This RAND study estimated multiple models for calculating how Air Force maintenance requirements change over time. Specifically, Pyles studied how aircraft age relates to maintenance and modification workloads and to material consumption. He used two conceptual models, looking first at the material consumption and workload for maintenance and then at modifications. Both models allow for varying effects at different aircraft ages, and Pyles took considerable effort to distinguish the actual age effect from other factors. He experimented with both linear and logarithmic dependent variable specifications.
Pyles used regression analysis to address several questions about age effects, including questions on how a fleet ages, if and how platforms age differently, the future prospects for cost and workload growth, and the age effect at different ages. He analyzed trends at many different levels including at the on-equipment, off-equipment, depot, and engine levels.
Excerpted from The Maintenance Costs of Aging Aircraft by Matthew C. Dixon Copyright © 2006 by RAND Corporation . Excerpted by permission.
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