Q: How does the Marine Corps use predictive analysis
and modeling to identify affordable technical
alternatives throughout a program’s life cycle?
A: The Marine Corps is using a model-based
systems approach and a variety of technologies
to improve the entire acquisition process.
By James smerchansky
Defense Department weapon sys- tems typically have a large num- ber of requirements with different
and competing relationships. These relationships are often difficult to identify
and may remain unknown before system
development and integration. modeling tools provide the department with
the capability to better understand the
relationships between cost, schedule, risk
and performance before requirements are finalized and major
costs are incurred. marine corps systems command (mcsc),
as the Department of the navy’s systems command for marine
corps ground weapon and information technology system
programs, is transitioning from a document-based, sequential
systems-engineering approach to a model-based engineering approach to better understand and inform requirements
prior to major milestones and contract awards. The foundation for this transformation has been the implementation of
model-based systems engineering based on the application of
the systems modeling Language (sysmL). mcsc developed a
unique sysmL-based tool, the Framework for assessing cost
and Technology (Fac T), which allows concurrent tradespace
analysis and incorporates the technological advantages of a
model-based engineering approach to acquisition.
Fac T is a government-owned, Web-based tool that provides
the framework to integrate disparate data and models into a
single-decision support environment that permits concurrent engineering and cost analysis. It allows for near real-time
first- and second-order assessments of the impacts on cost of
requirements, design and performance changes.
Fac T supports systems of systems engineering and applies
sysmL to identify dependency and interactions of require-
ments and system parameters. It then assesses the impact on
life-cycle costs resulting from changes to these requirements
and parameters to assist the decision maker in managing risk
while optimizing performance. FacT allows for bottom-up,
detailed system designs to be modeled, explored concurrently
in a top-down and cross-domain fashion, filtered and scored
against a set of dynamically assigned requirements.
mcsc uses Fac T, among other predictive modeling capa-
bilities, to support weapon system programmatic decisions.
These tools provide mcsc with the ability to examine multiple
risks as well as the potential cost, performance and logistics
impacts of executing particular courses of action throughout
the weapon system life cycle. conducting predictive analysis
during early stages of acquisition assists decision makers in
developing sound requirements with known impacts. This
analysis is also critical for legacy equipment during the sustain-
ment phase, which embodies the greatest life-cycle costs of a
weapon system. conducting predictive analysis throughout
the life cycle allows program managers to plan and execute
a course of action with a defined degree of confidence in the
resultant life-cycle cost and technical performance.
While the capability is maturing in knowledge and application—to include organic capability—the marine corps is
applying this predictive analysis strategy to support continuous
process improvement across the full range of actions required
to maintain and sustain ground equipment. as mcsc has
only recently begun this transition to a model-based engineering and sustainment approach, actual returns on investment
(rOIs) have not yet been formally realized and documented.
however, recent analyses indicate the potential for significant
rOIs, including the following examples involving Program
executive Officer Land systems marine corps programs:
• assault amphibious Vehicle (aaV) reliability-centered
maintenance analysis—currently demonstrating the benefits
of implementing changes to preventive maintenance checks
and services strategy for the aaV to include cost, availability and man-hours. This analysis validated the reliability-centered maintenance recommendations and identified the value
of conducting these analyses.
• high mobility multi-Wheeled Vehicle Depot study—
Potential $430 million cost avoidance through 2030 by ceasing
a schedule-based depot maintenance strategy and commencing with a demand-based strategy. analysis showed great
enterprise saving with a nominal impact to unit readiness.
• Logistics Vehicle system replacement sustainment strat-
egy—Identified strategy to achieve long-term objective of 90
percent material availability at lowest cost.
The use of a model-based systems approach coupled with
set-based design principles allow for a rapid, comprehensive
evaluation of a wide range of alternative system designs during
the early analysis phases of an acquisition program. a comprehensive analysis of alternatives that integrates cost, schedule
and performance trade-offs in a single data environment provides decision makers with a clearer understanding of risks,
requirements feasibility and affordability before major decisions that impact program life-cycle costs are made. Predictive
analysis, to include Fac T, is instrumental in mcsc’s plan to
efficiently and effectively execute acquisition programs according to Better Buying Power initiatives.
James Smerchansky is deputy commander for Systems Engineer-
ing, Interoperability, Architectures and Technology at Marine
Corps Systems Command. He is a member of the Senior Execu-
tive Service and chief engineer for the Marine Corps.
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