Maggie Gutierrez, James McCoog, and Timothy Zitkevitz, Lockheed Martin
Effective COTS Obsolescence Management and
Supportability
ABSTRACT
Establishing an effective, proactive obsolescence management program that can maximize supportability
of weapon systems is difficult. Logistics is often faced with an insufficient budget to address all of the
identified obsolescence issues. However, when the configuration contains COTS parts, the challenges are
larger and the stakes are higher. With the increase of COTS content in our programs, COTS obsolescence
processes have been put to the test, improved, and tested again. Today, the result is a set of processes and
supporting toolsets where the myriad of data needed to effectively predict, analyze, and address COTS
obsolescence issues is obtained, stored, updated, and reviewed on a systematic basis so that system
supportability is maintained, in a cost-effective manner.
INTRODUCTION
Fifteen years ago, when Secretary of Defense Perry mandated the use of COTS, he envisioned that
weapon system designs would be able to leverage COTS vendor R&D efforts to facilitate implementation
of the latest technologies while taking advantage of lower costs resulting from commercial market
competition (Perry 1994). While true, because military system life spans are far longer (and are getting
even longer due to budget constraints) than those of the commercial electronics parts used to build them,
there is a fundamental disparity that results in significant sustainment challenges and costs.
Traditional approaches to obsolescence management have been reactive. Before COTS parts became a
significant part of military designs, a typical approach for component obsolescence management was that
engineering completed the design, then part obsolescence issues were tracked, identified, evaluated and
resolved. This approach, while reactive, was generally sufficient to address the risks associated with
obsolete parts. It is not, however, sufficient to address the risks associated with a more dynamic COTSbased design.
Traditional mil spec based designs are frequently supported for 20, 30 or more years. Due to the short
vendor production period, it is not cost-effective to use the same approach for a COTS-based design. It is
far less costly to refresh the design periodically throughout the life of the system (Sandborn 2005). As a
result, the new focus of obsolescence management is the concurrent management of the inevitable
obsolescence issues and implementing a well-conceived technology refresh framework that minimizes the
cost of the system upgrades.
Ensuring that the resulting system can remain viable while meeting performance requirements and
minimizing Total Ownership Cost (TOC) demands careful planning and selection between the myriad of
evolving technologies. Studies have shown that 60 to 80 percent of the TOC is committed by decisions
made during the early stages of design as is clearly shown in Figure 1, below (OSD CAIV 2007).
Clearly, then, effective obsolescence management must begin during the design phase of a program. By
ensuring that supportability is considered at part selection, increased reliability and reduced total
operating cost can be realized.
1
FIGURE 1. Typical Program Lifecycle Costs (OSD CAIV, p. 2-1, Fig 2-1)
Lockheed Martin has developed a proactive and strategic approach to delivery of life cycle obsolescence
management services, from design through disposal, including specific tailored processes to address the
unique issues associated with obsolescence management of COTS parts. This approach is innovative
with respect to tools, processes, analysis, reports and metrics, and has improved cost-effectiveness while
minimizing production and fleet support issues.
The Lockheed Martin process has twice been recognized as a Best Practice by the U.S. Navy. In 2002, the
Naval Surface Warfare Center (NSWC) in Crane, Indiana found our processes to be an industry Best
Practice. In a January 2006 letter, Department of the Assistant Secretary of the Navy Logistics (DASNL), Nicholas Kunesh, stated that this process, as executed for the Aegis Weapon System, was a “Best of
Breed” to be emulated by others. The Lockheed Martin team has been most recently recognized for its
superior performance as part of the Aegis Weapon System (AWS) DMS Working Group and was granted
the DOD 2008 DMSMS (Diminishing Manufacturing Sources and Material Shortages) Team
Achievement Award.
SUCCESSFUL OBSOLECSCENCE MANAGEMENT
Establishing an effective, proactive obsolescence management program to maximize the supportability of
a military weapon system has its challenges. Logistics activities often have an insufficient budget to
perform a thorough surveillance of the system’s bill of material (BOM) list, let alone address all of the
identified obsolescence issues.
Obsolescence Management Process
The Lockheed Martin Obsolescence Management approach has evolved over time. The foundation
consists of a DMS Management Team (or DMS Working Group), performing DMS case management
using predictive tools and proactive processes which provide a framework for DMS case resolution. The
DMS Management Team processes are thorough and programmatic, yet nimble enough to react to
emergent issues. The approach is utilized from the design phase through disposal, and identifies
obsolescence issues early, allowing sufficient time to develop the optimum solution to address risk
resulting in maximized cost avoidance for its customers. It is innovative with respect to tools, processes,
reports and metrics, has improved productivity, and minimized production and fleet support issues.
2
In this section, the discussion focuses on the most basic element of life cycle obsolescence management
services. The basic obsolescence management process begins with monitoring and identification of DMS
issues, resolution identification and implementation, and finally, DMS case closure. Each DMS problem
must be evaluated to ensure that all reasonable resolution options are considered and a business case
analysis performed to determine the optimum resolution. The Lockheed Martin DMS case resolution
process is shown in Figure 2. Cost, technical, and schedule risk all play in part in case resolution
identification.
FIGURE 2. Basic DMS Case Resolution Process
COTS AND OBSOLENCENCE MANAGEMENT
While proactive obsolescence management recognizes that obsolescence issues need to be identified as
early as possible so that the timeframe for resolution evaluation and implementation is maximized,
designing systems to accommodate COTS hardware and software is very different from the “design by
requirements” of mil-spec and unique-development systems. Inherent in COTS is the ability to
potentially develop better systems with more life cycle flexibility and at a lower cost. Ensuring that the
resulting system can remain viable, while meeting performance requirements, demands careful planning
of the evolving technologies using a programmatic and cost-driven process that fosters supportability,
enhancement, and interchangeability of COTS items (Sandborn 2005).
Planning begins early in the life cycle of a system, influencing part selection decisions to ensure that
sustainability and total operating cost goals are met in conjunction with first cost and performance
objectives. Recognition that COTS items have relatively short life cycles due to rapidly changing
technologies and uncertain market demands and, in some applications provide mission critical functions,
has resulted in the need for more aggressive obsolescence management strategies, including a focus on
technology trends. These additional strategies have been put into a framework for successful COTS
obsolescence management and are shown in Figure 3 below.
3
Technology
Roadmapping
Technology
Transition
Market
Surveillance
Obsolescence
Forecasting
Product Selection
System Health
Assessments
Tech Refresh
Planning
TOC
Optimization
DMS Case
Management
FIGURE 3. Framework for COTS Obsolescence Management (Gutierrez, 2008)
The framework of the COTS Obsolescence Management process used by Lockheed Martin to specifically
address
COTS obsolescence includes:
 Monitoring / Market Surveillance
 Technology Roadmapping
 Product Selection Inputs
 Obsolescence forecasting & Health Assessments
 Asset Reutilization
 Technology Refresh Planning & TOC Analysis
 Monitoring Changing Global Regulations (RoHS, REACH)
 DMS case management and prioritization
Monitoring and Market Surveillance
To minimize the effects of a dynamic commercial environment, suppliers are contacted on a regular basis
to obtain data on products being used, to refresh existing data, obtain data on products considered for
future use, identify industry technology trends, corporate directions, monitor supplier viability, product
end of sale dates, etc (Bradley 2007). Vendors can be contacted in a variety of ways: by e-mail, phone or
in person. The frequency of vendor contact is dependent on part cost, risk to the program, and program
budget. If the end of sale of a product is within the upcoming 12-24 months, additional information is
obtained regarding the last order date, whether there is a replacement, when samples will be available (for
testing), when the replacement part will be in production, the cost of the new item, etc.
Some vendor representatives, when contacted for market surveillance information, are unwilling or
unable to provide end of sale forecasts for their products. However, most vendors are willing to provide
4
market entry dates and information on part maturity. From this information, either using an algorithm or
past experience with the product category, it is often possible to develop credible end of sale forecasts.
(Sandborn 2005)
Adequate understanding of technology, including technology introduction, evolution, and roadmaps, is
important to fully appreciate the maturity of the technology and its expected life cycle. The primary goal
of market surveillance is to identify obsolescence issues before they occur, allowing the program
sufficient time to assess alternatives and develop cost-effective resolutions.
It should be noted that, although there are currently no robust subscription obsolescence tools with COTS
market information, there is at least one in commercial development. At some time in the future, it will
be possible to implement a hybrid approach of automated surveillance supplemented by manual
surveillance.
Technology Roadmapping
The technology assessment process implements an integrated, Systems Engineering approach that teams
major disciplines in the design process to identify and mitigate COTS technical and life cycle risks (while
optimizing system costs). The fundamental element of this is technology roadmapping.
The goal of technology roadmapping is to ensure that, from a technology viewpoint, the long-term
sustainability of COTS-based design solutions remains viable. To accomplish this, system engineers
identify the key performance characteristics required and the candidate technologies associated with these
characteristics. Market research is then performed on these technologies to ascertain both their long-term
viability and Technology Readiness Level (TRL). The TRL, which is a measure of a technology’s
maturity, ranges from 1 (breadboard) to 9 (commercially available). Technology roadmaps are developed
for each of the candidate technologies to visually represent the results of these analyses. Roadmaps show
the technology’s viability over time, including follow-on technologies. These roadmaps, when used as an
input to the selection process, help to mitigate program risk through the early identification of potential
long-term sustainability issues, thereby reducing through life costs associated with product obsolescence.
After technology selection comes specific part selection.
Part Selection
COTS part selection occurs at the outset of a new program and/or when a program is implementing a
planned Tech Refresh event. The detail and formality of the selection process should be tailored to the
complexity and cost of the COTS product(s) being selected.
The product selection is typically accomplished through a cross-functional team approach. The various
subject matter experts on the team identify the selection criteria and the relative weighting of each of
these criteria. A typical selection team consists of representatives from system & design engineering,
supportability/COTS engineering, purchasing/sourcing, project management, production engineering, and
the customer (Bradley 2007).
Data from technology roadmapping and/or trade studies are reviewed in conjunction with performance
criteria, technologies selected, and vendor information. A part-specific criteria and weighting system
(“balanced scorecard”) is put in place, allowing IPT members to score the parts under consideration based
on vendor responses to a part-specific questionnaire. Typically, products being evaluated in this process
meet the technical performance, thereby allowing the selection team to place a greater weighting on such
things as long-term supportability, life cycle cost, supplier viability, etc. The result is a product selection
that is optimized, repeatable, unbiased, and justifiable. The results and recommendations are documented
and forwarded to the customer for concurrence.
5
Obsolescence Forecasting and Health Assessments
Information regarding COTS is dynamic. As a result, in addition to a robust and proactive market
surveillance effort, periodic health assessments must be conducted to review the current data (including
market surveillance data) in the context of its impact to the program.
The data needed to perform a health assessment on a system, subsystem, or piece of equipment includes:
 Stock information – program stock, OBAs, supply system stock
 Failure rates for all parts
 Configuration / configuration changes
 End of sale and End of vendor support forecasts
 Updated support spares modeling / impact date calculation, PBL contract implications
 Tech refresh plan (e.g. support period), extent to which asset reuse can be implemented
The number of spares needed to sustain the fleet to tech refresh can be calculated. This calculation takes
into account the program stock and stock in the supply system. It can also consider asset re-use (e.g. that
when a part is removed from equipment with an earlier tech refresh date, there will be asset reutilization
to support the equipment with later tech refresh dates, thereby reducing the total number of parts needed).
The value of COTS health assessments is in their application as program management communication
tools, most notably by providing graphical information which greatly simplifies the identification of
potential obsolescence driven supportability risks. Graphical depictions of health information are
discussed in a later section.
COTS Obsolescence Analysis Report (COAR)
The results of the supportability & obsolescence analysis of each COTS item used in the program are
documented in a COTS Obsolescence Analysis Report (COAR). It represents the latest “snapshot” of
available spares, failure rates, market surveillance data, etc. and is based on the most recent program of
record (fielding plans, tech refresh plans). The COAR, which is issued regularly (typically quarterly) to
account for the time-dependant nature of COTS market data, is provided to both program management
and government personnel and is comprised of five main sections:
 Summary / High Level System Analysis
 Current Tech Refresh Plan
 Obsolescence Curves (for each system / baseline)
 Health Charts (for each system / baseline)
 Baseline Assessments – summary of actions being taken to mitigate obsolescence risks
Obsolescence Curves
Obsolescence Curves graphically display system, baseline, or equipment health, at a particular point in
time. Although they are generated automatically from the Lockheed Martin COTS Database, they can
also be generated manually. The five zones depicted in an obsolescence curve are defined in Figure 4.
Status
In Production
Vendor Repair
Spares Support
Supportable
Not Procurable
Color
Definition
Percentage of parts which have not reached the End of Sale (EOS) date in each year.
Percentage of parts which have not reached the End of Support date in each year.
Percentage of parts which have not reached the calculated PFID (projected fleet impact
date) in each year.
Percentage of parts for which the PFID is reached in each year, but whose parts are still
procurable as of the PFID..
Percentage of parts for which sufficient support is not available through Tech Refresh and
the parts are no longer procurable.
FIGURE 4. Obsolescence Curve Key / Definitions
6
The obsolescence curve set includes four views of the information provided. The upper left Obsolescence
Curve shows the overall picture of the supportability/sustainability of the system in terms of the
percentage of items affected by some event each year. The other three charts are extractions of the same
information and are provided to make the data easier to read. A sample set of Obsolescence Curves is
shown below in Figure 5.
100%
80%
In Production
60%
Vendor Repair
93%
88%
40%
Spares Support
Procurable
74%
Not Procurable
42%
20%
29%
2010 2012
2014 2016
2018
2020
0%
21%
11% 11% 10% 8%
6% 6% 6% 3% 3% 3%
20
06
20
07
20
08
20
09
20
10
20
11
20
12
20
13
20
14
20
15
20
16
20
17
20
18
20
19
20
20
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
2006 2008
100%
100%
80%
80%
60%
60%
97% 96%
40%
100%
92% 90%
40%
78% 74%
60%
51%
20%
20%
8% 8% 8% 8% 7% 7%
33%33% 32%
26% 25% 24%
21% 19%19%19%19% 18%18%18%18%
0%
20
06
20
07
20
08
20
09
20
10
20
11
20
12
20
13
20
14
20
15
20
16
20
17
20
18
20
19
20
20
0%
14%
20
06
20
07
20
08
20
09
20
10
20
11
20
12
20
13
20
14
20
15
20
16
20
17
20
18
20
19
20
20
19%
FIGURE 5. Sample Obsolescence Curve
The green zones represent the declining percentage of parts which remain in production or that are
repairable over time. The yellow zone represents the percentage of parts that have not reached the stockout (PFID, projected fleet impact date) in each year. The cross-hatched zone represents the area where
risk can be mitigated if action is taken before the End of Sale date. (If spares are procured, this zone
would change to yellow.) The red zone is the area requiring immediate attention, representing the
percentage of parts that don’t reach PFID and the parts are no longer procurable, indicating that action
must be taken to identify potential solutions.
Health Charts
Health charts are more granular graphical representation of COTS products’ market status at a particular
point in time and are used to help identify and prioritize COTS issues and resolutions. The “health” is
represented by a color code indicating whether the product is in the supplier production period, supplier
support period, residual spares period, or stock-out. Health Charts can be used to display multiple or
single systems, and LRUs within the systems. They can be generated manually or can be produced by
tools such as the COTS Database.
The data that appears on a Health Chart is explained below in Figure 6 and a sample health chart is shown
below in Figure 7.
7
Status
Supplier Production Period
(vendor forecast)
Supplier Production Period
(engineering forecast)
Supplier Support Period
Color
Spares Attrition
Unsupportable/
Unsustainable
LRU has been replaced
DEFINITON:
Indicates the period during which a product is procurable, ending at the manufacturer’s
announced (or vendor forecasted) “end of sale.”
Indicates the period during which a product is procurable, ending with a forecasted
“end of sale” s not supplied by the vendor, but is forecasted by engineering.
Indicates the time when a product is no longer procurable, but is supported (e.g.
repaired, under warranty, etc.) by OEM, 3rd parties, etc.
Product is supported through spares attrition only (e.g. no longer procurable, no
supplier repair). The end of this period is the PFID (projected fleet impact date).
Indicates the time when the fleet may be impacted by the unavailability of spare parts.
This period starts on the PFID.
Indented blue text indicates that the part replaces the part immediately above it on the
health chart.
FIGURE 6. Health Chart Key / Definitions
2006
2007
2008
2009
REFRESH PERIOD
Notional X Notional X Notional X
ships
ships
ships
2010
2011
2012
OEM_PN
123456
DESCRIPTION 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4
CCA #1
67890
ASSY
AB2394
PART A
ST-659-X
ORIG PART
ST-660A REP. #1
ST-661B REP #2
324DC-3
PART C
845902-94- PART D
95825
PART E
68747698
PART F
MCN530
PART G
45IDZ92
PART H
69486BS PART H1
FIGURE 7. Sample Health Chart
The supplier production and support periods are shown in shades of green and are the result of market
surveillance activities. The spares attrition period is calculated taking into account parameters such as
failure rate, Quantity End Item (QEI), fielding profile, reuse profile, end of support date and available
assets (including both supply system stock and program-specific stock.) The spares attrition period ends
at the PFID date, after which the part is unsupportable (red).
The Technology Refresh period (shown as the shaded portion) is displayed so that stock-out events (prior
to tech refresh) can be easily identified. It should be noted that Health Charts do not identify the
likelihood of a follow-on product; rather they indicates the supportability of the current baseline
configuration, although such activities can be annotated on the chart.
DMS Case Prioritization
Since there is rarely sufficient funding to address all of the identified obsolescence issues in a proactive
DMS program, it is important to incorporate a technique for DMS case prioritization. (OSD-ATL 2003)
Lockheed Martin has developed a DMS case prioritization methodology which assigns weights to factors
such as: available assets, system criticality, field usage rate, number of LRUs impacted, modeled support
8
requirements, etc. The “scores” from each parameter are complied into an overall score which is used to
assign a priority to the DMS case.
An example of the prioritization methodology is presented in Figure 8.
System
Criticality
0 to 4
Case No.
605-1
668-1
503-2
541-4
1359-1
1228-1
1815-1
1852-1
16-2
1261-1
1847-1
1856-1
1173-2
587-2
1002-2
1326-2
1043-1
Repairable /
Consumable
0 to 2
Part No.
DMS Example 1
DMS Example 2
DMS Example 3
DMS Example 4
DMS Example 5
DMS Example 6
DMS Example 7
DMS Example 8
DMS Example 9
DMS Example 10
DMS Example 11
DMS Example 12
DMS Example 13
DMS Example 14
DMS Example 15
DMS Example 16
DMS Example 17
Notio
Description
DMS Sample Part 1
DMS Sample Part 2
DMS Sample Part 3
DMS Sample Part 4
DMS Sample Part 5
DMS Sample Part 6
DMS Sample Part 7
DMS Sample Part 8
DMS Sample Part 9
DMS Sample Part 10
DMS Sample Part 11
DMS Sample Part 12
DMS Sample Part 13
DMS Sample Part 14
DMS Sample Part 15
DMS Sample Part 16
DMS Sample Part 17
Case Status
nal Da
ta
Total
17
14
12
11
11
10
10
10
9
9
9
9
8
5
5
5
3
Immediately
Available Assets
0 to 4
Priority
High
Modeled
Support
Qty Required
0 to 4
Med.
Low
Refresh/
Redesign
Planned
-3 to 0
2-Year Field
Usage Rate
0 to 4
Number of
LRUs/NHAs
Impacted
0 to 4
FIGURE 8. Lockheed Martin DMS Case Prioritization Methodology Example (McCoog 2007)
The results of the prioritization can be complied into a matrix as shown in Figure 9. This prioritization
methodology has proven to be an excellent tool for managing a large number of DMS cases with a limited
budget andPRIORITIZATION
can be modified
based on FOR
a program’s
CASE STATUS ANALYSIS
METHODOLOGY
DMS CASESbudget (McCoog 2007).
PRIORITY SORT
No. Cases
As of 2007/07/02.15:08:50
Case No.
Part No.
Description
LC No.
Part No.
Description
605-1
DMS Example 1
DMS Sample Part 1
1067-2
20508652-707
Meg
Flash
Memory,SP
668-1
DMS Example 2
DMS Sample Part
2
Global
Memory
503-21118-2
DMS 20521003-1
Example 3
DMS
Sample
Part 3
1225-1
75343-1
Fan
Assembly,
541-4
DMS Example 4
DMS Sample Part 4Centri
1243-1
Resistor
1359-1
DMS RLR32C1001GS
Example 5
DMS
Sample Part 5
1228-1
DMS 2916266-1
Example 6
DMS
Sample Part 6
1301-1
Transformer,Pulse
1815-1
DMS 2898669
Example 7
DMS
SampleIntermediat
Part 7
1054-1
Amplifier
1852-1
DMS 2900278-3
Example 8
DMS
Sample
Part 8
1055-1
Dummy
Load,Electrical
16-21645-1
DMS 6710809
Example 9
DMS
Sample
Part 9WT CAS
Delay
Line,BIN
1261-1 DMS Example 10 DMS Sample Part 10
1646-1
6262322-3
Delay Line,Fixed
1847-1 DMS Example 11 DMS Sample Part 11
1660-1
7627498
Printer Assy,ADP
1856-1 DMS Example 12 DMS Sample Part 12
1827-1
Transformer Pulse
1173-2
DMS 2905188
Example 13 DMS
Sample Part 13
Microcircuit,Amplifie
587-21043-1
DMS 5616770-27
Example 14 DMS
Sample Part 14
1107-2
XSTAB
Assembly
1002-2
DMS 6379461
Example 15 DMS
Sample
Part 15
1154-1
Fan,
Assy;Part
VME16
1326-2
DMS 133-161-01
Example 16 DMS
Sample
1043-1
Example 17 DMS
Sample
Part
17 10
139-1DMS 013-X0062
Diode
Array,
Dual
1543-2
7011744
Case Status
Total Priority
Case Status Priority
17
14 High
12 HighHigh
11 High
11 High
10 High
10 Medium
10 Medium
9 Medium
Med.
9
Medium
9
Medium
9
8 Medium
5 Low
5 Low
Low
5 Low
3 Low
Microcircuit,MEM-FIFO
KEY for Case Status
High
Medium
Low
Priority
Priority
Priority
0
Totals
%
17
%
8
3
9
1
13
8%
28
67
6
101
59%
23%
8
28
4
40
39
113
19
171
23%
66%
11%
10%
CASE BREAKDOWN
LC Cases (MIL SPEC only):
92
Production Cases (MIL SPEC only):
Subtotal (MIL SPEC only)
LC Cases (COTS):
KEY for Case Type
Needs funding
LC (MIL SPEC)
Approaching completion
Production (LC impact, MIL SPEC)
Resolution in process
LC (COTS)
Resolution not identified
Production (LC impact, COTS)
FIGURE 9. Sample DMS Case Priority Matrix (McCoog 2007)
18
110
59
Production Cases (COTS):
Low
9
Total
9
2
Subtotal (COTS)
61
Total LC Cases
171
Sustainment and Tech Refresh Planning
Tech refresh (TR) is a planned system upgrade (or set of upgrades) performed at defined
intervals to address obsolescence issues by introducing new / interchangeable equipment. Tech
refresh planning is part of an overall sustainment strategy aimed at ensuring that a system with COTS
content is supportable at all times. Tech refresh is driven by the need to sustain or improve system
performance while minimizing both the cost and risk associated with supporting aging technology in a
constantly changing commercial environment.
The technology migration path is complex in that existing programs typically are in various stages of their
life cycle, many with huge investments, and are providing necessary, even critical, operational capability
that must be maintained. Having a viable TR plan is critical to the ability to maintain a system that is
technically capable, available, sustainable, and cost effective. Benefits of a good TR plan may include
smaller life-of-type buys as well as shorter availabilities needed for “major” refreshes.
A tech refresh plan is an important tool used to control many critical COTS elements in the architecture.
Some programs seek to optimize TR periodicity through Total Ownership Cost (TOC) optimization
where other programs prefer to set up a regular periodicity of refreshes on which to build a framework for
part selection optimization. A notional refresh schedule is shown in Figure 10.
US Navy
Year
1
CR3
TR2
D Year
US Navy
2
CR2
TR1
eploy
D Year
3
HCM
2009
2009
YEaeYear
Toronto
Hull
3loy
Yr 1
Calgary
Hull 2
Halifax
Hull
3
CR3
TR2
CR3
TR2
CR3
TR2
CR4
TR3
CR4
TR3
CR2
TR1
CR3
TR2
CR3
TR2
CR3
TR2
CR3
TR2
2010 2011 2012 2013 2014
BL1
BL1
CR4
TR3
TR3
CR4
CR5
TR4
CR5
TR4
CR5
TR4
CR5
TR4
CR6
TR5
CR6
TR5
CR6
TR5
CR6
TR5
CR4
TR3
TR3
CR4
CR4
TR3
CR4
TR3
CR5
TR4
CR5
TR4
CR5
TR4
CR5
TR4
CR6
TR5
CR6
TR5
2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
BL1
BL1
CR7
TR6
CR7
TR6
CR7
TR6
CR6
TR5
CR6
TR5
CR7
TR6
CR7
TR6
2025
2026 2027
2028
BL2
BL2
BL3
BL3
BL2
BL3
Montreal
Hull 4
Hull
5
Winn.
BL1
BL2
BL3
BL1
BL2
BL3
Hull
Fred.
6
Vancouver
Hull 7
Charlott
Hull 8 .
BL1
BL2
BL1
BL1
CR7
TR6
BL3
BL2
BL2
BL3
BL3
Ottawa
Hull
9
BL1
BL2
BL3
StHull
John
10’s
11 Hul
l12Q.
Ville
Hullde
11
BL1
BL2
BL3
BL2
BL2
BL3
BL3
BL1
BL1
6 year window
2 to 3 year window
2 to 3 year window
FIGURE 10. Notional Tech Refresh Schedule
In this example, ships were selected for refresh in the years indicated, resulting in a refresh cycle of
approximately 8 years. As can be seen from the chart below, the refresh plan calls for the equipment to
skip a Tech Refresh (TR); i.e., the equipment migrates from TR2 to TR4 and then TR6. This allows all
hulls to remain at the same configuration, thereby reducing the impact on logistics products and their
associated changes and minimizing through life costs. As new equipment is installed on each hull the old
equipment can be reclaimed to help support the not yet refreshed hulls of the same configuration. At each
refresh cycle there is the potential to introduce new technologies, whether to provide state of the art
equipment or to meet new functional requirements. In either case, integrating the part selection process
with refresh planning will result in optimal system design at minimum sustainment cost.
Benefits of Asset Reutilization
Implementation of an asset reuse strategy can reduce costs associated with COTS obsolescence
management. An asset reuse program identifies parts that can be reclaimed from test labs, ships, etc.
which are upgraded (refreshed) earlier in the tech refresh period to provide support for ships which are
refreshing later, thereby reducing the total number of parts that need to be procured. Depending on TR
10
periodicity and commonality of parts, an effective asset reuse program can offer significant savings of
downstream supportability costs.
Figure 11, below, demonstrates the benefits of asset reuse. The asset reuse case is depicted by the orange
line, reflecting the reclamation, testing and reissue of parts into the supply system as ready for issue (with
an allowance for reclaimed parts which cannot be certified as ready for issue). The model where reuse is
not utilized is defined by the blue line, showing the need to procure additional parts to provide support
until the next tech refresh.
% of Cost Normalized to 8 Yr Refresh w/ Reuse
600%
550%
500%
450%
Includes Reuse
400%
No Reuse
350%
300%
250%
200%
150%
100%
Normalized costs to 8 year TR cycle
50%
0%
0
2
4
6
8
10
12
14
16
18
20
22
24
Years from 1st Ship Leaving the Yard Until Tech Refresh Happens
FIGURE 11. Cost of Spares Over Time
Assuming a nominal 8 year refresh cycle, a study of one program’s data determined that spares
procurement costs are 80% higher if no reuse of parts is done. Another way to interpret this graph is that
for the same spares procurement cost, incorporating reuse into the lifecycle strategy will add about 4
years of support at little cost.
Although the cost of spares is fairly linear over time, funding to purchase those spares (or qualify the next
generation parts) is needed early in the production cycle, as COTS components typically have short life
cycles. This high upfront cost may make it cost-prohibitive to increase the time between refreshes as well
as limiting the upgrade path of the platform. Purchasing substantial quantities of spares through a lifetime
buy has significant risk because the procurements are often made prior to or at initial deployment when
failure rates are based solely on analysis (predicted), with little or no actual in-service experience.
Figure 12 shows obsolescence data over time. The blue and gold bars show the percentage of unique and
total parts that go end of sale each year, respectively, where the green bar shows the total annual cost
impact. All parts were still available within three years of product selection, but during the 4th year,
products started to reach end of life. Though only a few unique items were impacted (4%), these part
types made up 12% of total parts and 33% of the anticipated cost of all spares. These parts include hard
drives, display equipment, and printers, which are upgraded frequently by COTS manufacturers. Hard
drives and display equipment typically have a higher failure rate than many other COTS equipment types.
This combined with early end of sale dates increase the cost and amount of spares required.
11
100.0%
90.0%
80.0%
70.0%
Unique Parts %
60.0%
Total Parts %
Total Cost %
50.0%
Cumulative Unique %
Cumulative Parts %
40.0%
Cumulative Cost %
30.0%
20.0%
10.0%
0.0%
-4
^
Product
Selection
^
-3
^
Development
and Test
Sites Buys
^
^
-2
^
1st Ship
Buy
^
-1
0
1
^
1st Ship
Leaves Yard
2
3
4
^
Last Ship
Upgraded
5
6
7
8
9
10
^ Year (-4 = Production Selection,
^
Program
0 = 1st Ship in the Yard)
FIGURE 12. Obsolescence over Time
Most of the parts are obsolete by the Year 4 (eight years after part selection), which for this program, was
the time that the last ship is upgraded. Based on this data, 50% of spares cost will be incurred during Year
1 (five years after part selection), which for this program, was the first year after the ship exits the yard,
and 95% by year eight, the time the last ship is upgraded. This evaluation was based on the assumption
that replacement products will not be qualified for use even though there are some products (such as hard
drives) that will have follow-on offerings. Consideration of qualified replacements would push the
obsolescence curves slightly to the right, but they are still likely to remain within or just after the fouryear install cycle.
The total number of spares required peaks at Year 0 (four years after part selection). It also represents the
year requiring the 2nd highest funding requirement. This time period coincides with the typical lifespan of
commercial servers and storage devices (4-5 year life). These products are used in higher quantities
which drives the number of spares.
By the end of Year 1 (five years after part selection) 45% of the unique parts will become obsolete, the
highest number of unique parts becoming obsolete in any year. Networking equipment and server
infrastructure equipment (bladecenters, server power supplies, single board computers) all are predicted to
go end of sale. Though these parts have lower failure rates than other equipment, significant
requalification costs are typically associated with many of these parts, often resulting in a life time as the
most cost-effective resolution.
With the significant costs associated with both lifetime procurements and refreshes, a decision on the
length of service for a particular baseline (set of hardware) is necessary early in a program. Changing the
length of time a baseline must be supported will impact the POMing, funding and budgeting process.
Further, if the refresh periodicity is extended after a baseline is fielded, additional cost and risk is
introduced via increased use of aftermarket suppliers (and associated counterfeit part concerns).
12
As more complex weapon systems migrate to a truly COTS environment, the ability to procure products
after the end of sale date will diminish. Older legacy COTS weapon systems, though COTS-based, were
comprised primarily of niche COTS, and have allowed flexibility on supporting hardware well after the
true End of Sale dates.
Monitoring Changing Global Regulations (RoHS, REACH)
The EU’s RoHS Directive, effective July1, 2006, addresses “the restriction of the use of certain hazardous
substances in electrical and electronic equipment.” This directive bans the placing on the market of new
electrical and electronic equipment containing more than agreed levels of heavy metals such as lead,
cadmium, mercury, etc.
REACH (Registration Evaluation and Authorization of Chemical Hazards) is the latest EU legislation
requiring registration, evaluation, restriction of chemicals. Both chemicals and metals are involved and
its implementation is expected to be more costly than RoHS. The global transition to RoHS/REACH
compliant products impacts DoD programs and has an enormous potential impact to obsolescence. Even
thought military equipment was exempted from RoHS scope, the migration to COTS based systems and
the allowance of the usage of non-Military grade components brings RoHS issues to the forefront.
An obsolescence management program should treat material issues related to RoHS/REACH as DMS
issues since a supplier’s system qualified product offering is no longer available. The change to
RoHS/REACH compliant materials are to be evaluated to determine the impact on the manufacturing and
repair process, and on maintaining the system’s qualification status before accepting the altered product
into the system configuration (Abrams 2005). RoHS/REACH impacts may result in system configuration
and drawing changes if the supplier implements a new part number for the product.
DATA MANAGEMENT
Effectively managing COTS Obsolescence requires access to a significant quantity of data. Without a
structure in which to house and maintain the data, replete with the capability to easily access necessary
information for analysis, it is easy to become overwhelmed by the data. In fact, it can easily become quite
burdensome. The Lockheed Martin COTS (COTS Obsolescence Technical Sustainment) Database is used
by a number of programs to keep COTS data organized and to facilitate sharing of data between programs
(as allowed).
Data Requirements
Raw data must be collected for each part, including all relevant part numbers, NSN/NIIN, vendor
information, SMR code, failure rate, configuration data (usage and quantities) , fielding data, tech refresh
plan upgrade dates, market surveillance data, program and supply system spare counts, replacement part
strings, and so on. From this raw data, other information data can be developed, such as modeled spares
forecasts, stock-out date forecasts, etc.
COTS Database Organizes Data
Data organization facilitates access to and an improved ability to analyze the data itself. The COTS Data
Management tool organizes data for over 3,000 parts into categories, such as:
 Part Numbers: part number, vendor (OEM) part number, NSN/NIIN, altered item part numbers
 Vendor Info: Vendor Name, Cage, Address, Contact Name, Contact Info, Web Page
 Market Info: End of Sale, End of Support, Unit Cost, Vendor Contact History / Data
 Provisioning: Program and Supply System Spares info, SMR code
 RMA & Modeling: Failure Rate; Spares Required, Excess/Shortfall, Stock-Out Forecasts
 Configuration Data: Usages and Quantities
13




Obsolescence: DMS Case Information, Obsolescence Action Summary
Associated documents: End of Sale notices, test results, vendor correspondence
Replacement Part String: Relates Parts to Replaced / Replacement Parts
LRU / Constituent String: Relates Key Constituent Parts to Tracked LRU
COTS Database Capabilities
In addition to housing volumes of data, the COTS Database generates a number of reports, metrics,
graphics, and queries to facilitate analysis and generates automated notifications for specific tasks and/or
data changes. Some of the reports, graphics and queries that can be generated on demand include:
 Obsolescence Curves: Can be generated by program, baseline, equipment or vendor
 Health Charts: Can be generated by program, baseline, equipment or vendor
 Obsolescence Analysis Charts: Can be generated by program, baseline, equipment or vendor
 User-Defined Queries: Can be generated on demand (very flexible)
 Vendor Report: Parts, Descriptions, End of Sale dates for user-selected vendor(s)
The COTS Database automatically generates reports and alerts based on time schedule or if specific
conditions are met, including the following:
 Weekly Market Surveillance Reports: Provides list of contacts to be made based on frequency
 Weekly Part Review Report: Provides lists of weekly part checks to ensure each part is addressed
 Automatic Notifications: Generates e-mail to the team when end of sale data is changed to within
24 months, when spares modeling or failure rates change, etc. Notifications are user definable.
Funding Forecasting
Having a credible process to forecast obsolescence costs is critical to a program’s ability to obtain funding
for its obsolescence management efforts. The data used to generate program health information can also
be used as the basis to forecast funding requirements. Modeled shortfalls and unit prices can be used to
predict costs, while the end of sale dates obtained from market surveillance can be used to predict the
year(s) in which the costs will be incurred. For parts where a follow-on part is likely, a qualification can
Sample Financial Projection List
be
forecasted instead of a procurement. Figure 13, below, is an example of a funding forecast.
Key
LTB/BB
Qualification
Projected Expenditures by FY
IDs
DESCRIPTION
PN
EOS FY
Spares short/ex
req
tra
buy_qty
FR
Unit Cost
Extended
Cost
Assumption
FY10
Follow-on product should be available.
Assume minor qualifications in FY12
and FY15
1
CCA #1
xxxxxxxx
2012
10
90
70
70 $ 10,000 $700,000
2
CCA #2
xxxxxxxx
2010
2.5
20
15
15 $ 3,000 $ 45,000 LTB in 2010
3
CCA #3
xxxxxxxx
2015
1
30
30
30 $ 1,200 $ 36,000 LTB in 2015
4
CCA #4
xxxxxxxx
2011
5
200
140
5
CCA #5
xxxxxxxx
2012
5
50
35
6
CCA #6
xxxxxxxx
2010
15
30
30
160 $ 1,000 $160,000
20 $ 20,000 $400,000
Assume no follow-on product. LTB in
2013.
CCA #7
xxxxxxxx
2013
0.5
10
10
10 $ 15,000 $150,000
8
CCA #8
xxxxxxxx
2012
3.5
75
60
60 $ 1,200 $ 72,000 LTB in 2012
9
CCA #9
xxxxxxxx
2013
4
10
10
10 $ 10,000 $100,000 LTB in 2013
CCA #10
xxxxxxxx
2014
7
25
25
20 $ 7,500 $150,000
FY15
FY16
$ 50,000
$ 160,000
$ 52,500
$ 100,000
$ 400,000
$ 150,000
$ 72,000
$ 100,000
Minor qualification in FY14 and buy in
FY16 (lower qty).
FIGURE 13. Funding Forecasting
FY14
$ 36,000
FY10
Total by FY $ 145,000
Subtotal LTBs $ 45,000
Subtotal Qualifications $ 100,000
14
FY13
$ 50,000
35 $ 1,500 $ 52,500 LTB in 2012
Medium complexity qualification in
FY10 and buy in FY14 (lower qty).
FY12
$ 45,000
FR seems low. No follow-on product.
Assume buy in FY11.
7
10
FY11
FY11
$ 160,000
$ 160,000
$
-
FY12
$ 174,500
$ 124,500
$ 50,000
FY13
$ 250,000
$ 250,000
$
-
$ 50,000
FY14
$ 450,000
$ 400,000
$ 50,000
FY15
$ 86,000
$ 36,000
$ 50,000
$ 150,000
FY16
$ 150,000
$ 150,000
$
-
The funding forecast in Figure 13 depicts a format for documenting the basis of a funding forecast which
includes the elements of funding projections (e.g. the end of sale year, failure rate, unit cost, and modeled
shortfall) as well as any clarifying assumptions. Procurements and qualifications are distinctly indicated
so that totals by year can be calculated. This analysis can be further delineated by adding case priority
information too.
Metrics
Selection and use of meaningful DMS metrics has become an increasingly important aspect of
Obsolescence Management. DMS Metrics are used to provide information on the current DMS Program
status, provide insight into what trends are occurring and to demonstrate the value of the DMS program.
Program metrics can include the following:
 Caseload – active, new, resolution identified, closed
 DMS Case Identification Trends
 DMS Case Resolution Trends
 COTS vs. non-COTS Caseload
 DMS Case Aging Report
 Cost Avoidance
Sample metrics can be found in Figures 14, 15, and 16 below.
DMS Caseload Metric Example
160
140
100
80
60
40
20
Closed
Resolution Identified
FIGURE 14. DMS Caseload Metric Example
15
08
g
l0
8
Au
Ju
Active
Ju
08
n
08
M
ay
8
r0
Ap
08
M
ar
Fe
b
08
08
Ja
ec
D
N
Opened
n
07
07
ov
07
O
ct
pt
0
7
0
Se
Number of Cases
120
180
Total Number of Active Cases
160
140
120
100
80
60
40
20
Se
pt
06
O
ct
06
No
v
0
De 6
c
06
Ja
n
0
Fe 7
b
07
M
ar
07
Ap
r0
M 7
ay
07
Ju
n
07
Ju
l0
Au 7
g
0
Se 7
pt
0
O 7
ct
07
No
v
0
De 7
c
07
Ja
n
0
Fe 8
b
08
M
ar
08
Ap
r0
M 8
ay
08
Ju
n
08
Ju
l0
Au 8
g
08
0
FIGURE 15. COTS
COTS Vs. Non-COTS
DMS Caseload Metric Example
MIL Spec
Replace on Failure
Reclamation
N/A (No Additional Action Required)
Replacement Supplier - MILSPEC
Replacement Supplier - COTS
Replacement Part - MILSPEC
Replacement Part - COTS
LTB / BB - MILSPEC
LTB / BB - COTS
Excess Stock - MILSPEC
Excess Stock - COTS
0
20
40
60
80
100
120
140
160
FIGURE 16. DMS Case
Resolution
by Type
Metric
Example
Number
of Cases Closed
to Each
Resolution
Type
CONCLUSION
FY2006 Total
FY2007 Total
FY2008 Total
Establishing an effective, proactive
COTS obsolescence
management
program can help maximize the
supportability of weapon systems while minimizing unexpected life cycle costs. Lockheed Martin has
been successful in managing COTS obsolescence for its customers using a combination of market
surveillance, regular data updates and analysis, robust tools, and a viable tech refresh plan. While these
capabilities are facilitated by Lockheed Martin developed tools, the concepts can be adapted to suit other
programs’ existing tools, databases, etc.
16
REFERENCES
Abrams, Fern, “Implications of European Union’s RoHS Directive and the Move to Lead-Free
Electronics”, DMSMS 2005
Bradley, Maureen, Albert Montemuro, and Daniel L. Ceretti, “Coping with COTS - Preparing for
Potential Pitfalls when using COTS in Legacy Military Systems”, Asia Pacific Systems Engineering
Conference, 2007
Gutierrez, Maggie, “The Complexities of COTS Obsolescence Management”, DMSMS 2008 Conference
McCoog, James R. and Maggie Gutierrez, “Effective Obsolescence Management Strategies to Optimize
Operation Availability”, DMSMS 2007 Conference
McCoog, James R. and Melissa Singleton, “DMSMS Management Program for the Sustainment of the
AEGIS Weapon System”, DMSMS 2008 Conference
Office of the Secretary of Defense Cost Analysis Improvement Group, “Operating and Support CostEstimating Guide”, October 2007
Office of the Under Secretary of Defense, Acquisition, Technology & Logistics, “Diminishing
Manufacturing Sources and Material Shortages (DMSMS) Guidebook”, SD-22, November 2006
Perry, William J, “DoD Policy on the Future of MILSPEC”, Memorandum, June 1994
Sandborn, Peter and Parmeet Singh, “Forecasting Technology Insertion Concurrent with Design Refresh
Planning for COTS-Based Electronic Systems”, Proc Reliability and Maintainability Symposium, 2005.
Sandborn, Peter, F. Mauro and R. Knox, “A Data Mining Approach to Electronic Part Obsolescence
Forecasting,” DMSMS 2005 Conference
ACKNOWLEDGMENTS
We would like to thank the following members and former members of the Lockheed Martin COTS and
Obsolescence Management team for their contributions to the development and long-term success of our
Obsolescence Management program: Maureen Bradley, Dennis Genaw, Joanne Smith, and Curt Weller.
BIOGRAPHIES
Maggie Gutierrez is a Systems Engineer within the Global Sustainment organization of Lockheed
Martin MS2. She earned a bachelor’s degree in Mechanical Engineering at Lafayette College.
James R. McCoog is a Systems Engineer within the Global Sustainment organization of Lockheed
Martin MS2. He earned a bachelor’s degree in Electrical Engineering from Drexel University, and a
Masters in Management from Steven’s Institute of Technology.
Timothy J. Zitkevitz is a Systems Engineer within the Global Sustainment organization of Lockheed
Martin MS2. He earned a bachelor’s degree in Systems Engineering at the University of Virginia and a
Masters of Engineering Management at Old Dominion University.
17