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Project Announcement: Enterprise Machine Learning for Predictive Asset Readiness

The US Department of Defense is partnering with industry and academia on an initiative to forecast readiness and learn the drivers of levels of readiness consumption of Armored Brigade Combat Team (ABCT) equipment and present this information in a Common Operating Picture (COP) or other system for use by logistics and operations planners.

The industry partner will be required to translate the predictions and drivers into readiness consumption forecasts and recommended actions to be used by maintenance and sustainment personnel at multiple echelons to improve unit readiness during pre-deployment training, coming into and during National Training Center (NTC) rotations.

Specific objectives of this work are as follows:

  • Provide readiness predictions for individual Armor assets over specified time horizons, individually and aggregated to Brigade, Division, and Corps levels as appropriate.
  • Identify the drivers (i.e., model factors) of predicted downtime and delays in repair time, also at individual asset and aggregated levels.
  • Incorporate past mission data into the predictive model to discover and quantify the impact on readiness of past mission parameters, environmental factors, and other operational factors as may be available in source data.
  • Integrate the predictions and drivers as described above to support planning scenarios that emulate past mission parameters.
  • Determine the required staffing, training, and process changes that will support full adoption of these new capabilities within specific locations and anticipate similar changes that will be required for a future expansion.
  • Quantify and document the efficacy of this solution in improving the predictability of readiness and increasing levels of readiness, along with the key success factors in realizing these benefits.

If you feel your organization has the technical capabilities and would like to be considered for this project, please complete the form below and upload your organization’s technical capabilities statement.

Interested Submissions Due by 7/23/24.

We encourage participation of Disadvantaged Business Enterprises (DBEs), including Minority Business Enterprises (MBEs) and Women’s Business Enterprises (WBEs).

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