Technical Report
Systems Engineering for Contingency Basing
-
Systems Engineering and Systems Management Transformation
Report Number: SERC-2012-TR-033-1
Publication Date: 2012-11-30
Project:
Contingency Basing
Principal Investigators:
Dr. Brian Sauser
Co-Principal Investigators:
Dr. Robert Cloutier
Tactical Small Units (TSU) (battalion [300-1000 soldiers] and
below) currently establish non-standardized base camps for contingency
operations (contingency basing), potentially limiting their ability to efficiently
employ Full Spectrum[1] operations
by placing the TSU with reduced capability. The TSU may not be able to
effectively support the modern Full Spectrum battlefield demands unless
contingency basing capabilities specific to the TSU are combined as a single,
integrated, agile, force projection platform. A contingency base should provide
Soldiers with an effective, logistically supportable, affordable, and rapidly
deployable environment to project force across the Full Spectrum of operations.
The U.S. Army Research, Development and Engineering Command (RDECOM) and the
various Program Executive Office (PEO) and Program Management (PM) stakeholders
working together must develop a contingency basing capability – along with a
development planning process -- that will enable an Army enterprise approach to
capability delivery for the tactical edge with total system integration aligned
to Army Modernization strategies and ARFORGEN (Army FORce GENeration). As such,
the U.S. Army’s transformation and force structure changes have resulted in a
reduced capability regarding training, planning, management and expertise
available to the Army units as they establish, maintain, sustain and transition
a contingency base through its life cycle.[2]
This research focused on specific aspects of Tactical Small
Unit-Contingency Basing (TSU-CB), as a force projection platform and a
potential means to address the interrelated individual Soldier and TSU load
(cognitive and physical) using methods and tools developed for systems
engineering. The research task is to develop a set of interrelated processes,
mechanisms, and tools to capture, explain, and manage the complex operational
and system interaction posed by the dynamic nature of the TSU operations, along
with a means to measure progress. The TSU exhibits a complex, pluralistic, set
of requirements across a number of factors ill-suited to standard system
engineering practices. Novel means to optimize TSU-CB need to be considered.
The primary operational outcomes being sought are:
- Reduced vulnerabilities and
losses: Human, systems, and information
- Reduced sustainment demands: Substantially
reduce supply convoy requirements by implementing self-sustaining and
“right-sized” basing capabilities with special emphasis on fuel, water and
waste.
- Cost effective choices and
solutions: Innovation that targets life cycle affordability;
sustainment cost savings re-directed to resource DOTMLPF integrated
solutions.
- Effectively trained and ready
Soldiers and planners with contingency basing skills effectively
distributed throughout the Operating and Generating Force.
- Reduced Contingency Basing
manpower burden on operational mission forces: yielding a Force
Multiplier effect.
- Reduced time, material,
equipment and personnel requirements for Base Construction/
Deconstruction: Modular, scalable, adaptable; re-deployable “fighting
bases.” Informed by existing
contingency construction planning and management systems and tools.
- Enhanced interoperability with
Joint, Inter-Agency, Inter-Governmental and Multi-National (JIIM)
partners. Informed by coalition partner practices.
- Reduced Environmental, Safety and Occupational Health (ESOH) Risks.
The processes and tools need to enable the measurement and assessment of improvements based on new and emerging technologies that will be integrated as capability packages into the ARFORGEN process.
Thus, this research was a collaboration among the Systems
Engineering Research Center (SERC), RDECOM and its respective Research and
Development Engineering Centers (RDECs), Army support functions (such as PEO
Combat Support & Combat Service Support, Training and Doctrine Command, PEO
Integration, and Assistant Secretary of the Army for Acquisition, Logistics and
Technology, to name a few), and the Army user community. Below are seven sub tasks
that were in response to the above stated eight objectives. For the first
year of this research task, only three of the sub tasks were executed and will
be reported up on in this Final Technical Report. All sub-tasks are summarized below, and those
sub-tasks not supported are identified in italics.
1. Focus
on initial system boundaries and connections in order to facilitate early
dynamic modeling. In order
to separate the critical few from the trivial many, SERC shall work with NSRDEC
researchers and chief engineers to create an abstraction of the whole
Contingency Basing and Soldier Load scope that can be animated at a early stage
as a guide to identify the critical components and aspects that will need
priority of scrutiny on order to create high-fidelity models. This will be
achieved by creating high-level systemigrams and system models for Soldier load
and Contingency Basing. In addition, identify means to create initial
value/risk based design objectives and functions on a reduced (and thus
manageable) constraint space. Consistent with this work, SERC will provide
expert input to capability capture, analysis and value risk capture.
2.
Model-based systems engineering (A). As
Contingency Basing is emerging, there is a proliferation of separate,
individual models: business case/cost, functional decomposition, virtual,
logical, Sandia logistical support, and SysML, to name a few. It will be
difficult to keep these models in synchronization -- linked – especially during
the early work on this initiative. A
conceptual framework for “holistic” modeling support for complex initiatives
such as Contingency Basing need to be explored. In addition, SERC could help
the Army create specifications for the interoperability of the many CB models,
an area of active research. The goal is to anticipate model compatibility
problems and prevent them. Furthermore, the model-based system could be used to
look for patterns, such as program protection exposure, architecture for
resilience, incomplete vignettes, and technology insertion candidates.
3.
Model-based systems engineering (B).
Network models will be created to identify features that belong
together. Contingency basing is awash in functions, tasks, views, data,
connections, causes, time orderings, priorities, and linkages. Have any been
missed? One way to ascertain this is to ask a wide scope of experts who
normally operate in siloed organizations about what should be connected to what
else -- using social networking tools. The collective linkage network can then
be interrogated to see if the already documented connections account for the
clumps, cliques, and cluster suggested by an array of specialized experts. In addition, a specific perspective to
prioritize functions will be provided relative to a number of dimensions, such
as time-ordering, socio-political factors, regulations, doctrine, etc.
4. Help assess and formalize Developmental
Planning Process and Practices within the US Army.
Based on the established and piloted Air Force Research Laboratory’s Concept Characterization
and Technical Description process (its version of early life cycle
Developmental Planning, Air Force Research Laboratory Instruction 61-104,
Science and Technology), SERC researchers will work with the Contingency Basing
leads to tailor this early systems engineering standard to Army needs. The Air
Force standard is one of the few early SE development processes that has been
in place long enough for lessons learned to accumulate and to inform both the
standard and its application in the science and technology area.
5. User CB workbench. In
addition, the model-based system would function as a user workbench where a
combatant commander could explore options for configuring contingency bases.
While there would be significant computing capability “under the hood,” the
user would see models only in his/her terms. And as field knowledge of
contingency bases grows, the workbench would grow in fidelity and decision
support. SERC will help to create the specification and pilot instances of this
Workbench.
6. Visualizing an “infinity” of data.
All of the permutations and combinations of the input space will produce a
flurry of base configurations. How will one be able to make sense of all of the
combinations of inputs and then be able to react sensibly to the output?
Visualization technology helps engineers see patterns in high-dimensional data.
Imagine all of the possible outcomes with just the few input categories
suggested by the Corps of Engineers: time, size, mission type, base systems,
operations tempo, and human dimensions, resulting in a spectrum of
recommendations about configuration and duration (expeditionary, temporary, and
enduring). To this add the vagaries of the consumption data, such as water per
day per Soldier, energy consumption per day per Soldier, etc. SERC will aid the
Contingency Basing team experiment with and weigh features of visualization
systems as a way to reason from the dense space of data.
7. Assessment and improvement of SoS
engineering methods. Validation and verification (V&V) of Contingency
Basing concepts and early formulation will be difficult because in its
current form it is an applied practice, the kind that can best be validated
only in the field, such as at the Systems Integration Lab at Ft. Devens. But
that would be very late in the conceptual life cycle to find errors, so a form
of early V&V is required. SERC researchers working with the Army would
develop improved verification and validation approaches for SoS via models and
formal methods. It would be desirable to
verify and validate at the functional level, rather than delay every time to
the final material solution. It would
also be desirable to understand a model based paradigm that allows a more
expedient synthesis, analysis, and evaluation of the problem and potential
array of solutions, and allow trade space exploration and a better
understanding of the resilience of the architecture and deployment.
Accordingly, we propose an exploration of deep systems engineering practices
that would formalize the characterization of testable properties as a long-term
improvement for what will appear as conventional engineering in the early days
of the Contingency Basing initiative.