The Sustainment Management System (SMS) is a web-based software application developed by ERDC’s Construction Engineering Research Laboratory (CERL) to help all real property asset management stakeholders - from civil engineers, technicians and managers to
headquarters - decide when, where and how to best maintain existing infrastructure. Because assets are so vast and diverse, a “knowledge-based” philosophy drives the SMS process.
The process starts with a collection of real-property data, a detailed component
level inventory (either modeled or collected) that identifies their key life cycle attributes such as the age and material, and typically a field assessment (through an objective and repeatable process) to gather real-world performance of these components.
From this inventory and assessment information, Condition Index (CI) metrics for each component are predicted based on its expected stage in the life-cycle. The level of detail and frequency of subsequent inspections can be varied based on component criticality,
expected vs. measured condition, rate of deterioration, and remaining service life. In addition to these condition assessments, functionality assessments can be performed to evaluate user requirement changes, compliance and obsolescence issues. This provides
a comprehensive picture of the overall performance of assets and their key components.
Utilizing the projected condition index of all of the components within a facility, the SMS process provides the capability to construct detailed work identification and prioritization rulesets to provide system users with recommended work candidates and their estimated cost up to 10 years into the future. Additionally, multiple configurations can be executed to compare/contrast the impact of various courses of action. Whether the configurations change in terms of available funding or changes in acceptable thresholds for component condition, the SMS toolset allows for rapid analysis of the outcomes of each path allowing for better informed decision making.
On-going work refining the art of asset management through algorithm and process development, data mining, and similar research efforts.
Taking new asset management practice discoveries and building tools that are leveraged by our industry partners.
Provide Federal agencies assistance and guidance in the implementation of SMS tools and processes for maximum effectiveness.
Application hosting, SMS Support helpdesk, and the various efforts required to provide SMS tools to Federal agencies.
CERL develops the procedures for measuring the condition of airfield pavements, resulting in the Pavement Condition Index and the accompanying Micro Paver management software.
A similar methodology to PAVER was adapted and applied for a Roofing Condition Index (ROOFER), a Track Structure Condition Index (RAILER), and a Building Condition Index (BUILDER).
Early pilots to adopt BUILDER SMS with the US Navy and US Marine Corps commence.
An SMS approach to shorefront infrastructure is developed.
The Office of Under Secretary of Defense for Acquisition, Technology, and Logistics issued a policy requiring all of DoD to implement SMS as the standardized process for facility condition assessment.
Research begins to construct a database platform capable of performing SMS asset management across all real property domains.
Work begins to build out the SMS approach for site utilities, fuels distribution, and other civil infrastructure assets. This work laid the foundation for the Enterprise SMS (ESMS) platform.
When fully developed and deployed, the ESMS platform will provide cross-domain SMS capability for all applicable real property domains, vastly increasing the power of SMS analytics for optimum facility asset management.
Today there are over 1.3B square feet of building assets under management with BUILDER SMS.
Development of the Enterprise SMS continues to support the Fuels and Utilities real property domains and will eventually become the centralized tool for all SMS real property domain analysis.
Additionally work is underway to include dams, levees, and dikes (water rention structures) and shorefront infrastructure in the Enterprise SMS platform
With a vast and growing dataset of real property component data, there are immense opportunites for further research on component degradation behavior through machine learning and artificial intelligence
that will ultimately provide refined lifecycle models for more accurate condition and work candidate projections.
Significant opportunity also exists for further development of the work candidate identification and recommendation process to ensure that our stakeholders maximize their objectives while minimizing the inputs to get there.