Artificial Intelligence/Machine Learning, ASA(ALT), Phase I

AI-Enhanced TPS Development and Sustainment

Release Date: 06/11/2024
Solicitation: 24.4
Open Date: 06/26/2024
Topic Number: A244-034
Application Due Date: 07/30/2024
Duration: Up to 6 months
Close Date: 07/30/2024
Amount Up To: $250,000

Objective

This Army SBIR project will develop field-level maintenance and repair of weapon systems electronics that shorten supply chain latency for electronic component repairs. The solution must screen electronic components for no evidence of failure at the source in the tactical unit.

This mitigates the high cost of discovering NEOF at higher echelons of maintenance. The Army wants faster weapon system repairs, faster component turn-around-times, high equipment operational availability and high unit readiness at lower life-cycle costs.

The Army is transitioning to a warfighting doctrine of Multi-Domain Operations in Large Scale Combat Operations. This doctrine emphasizes the vulnerability of contested Logistics supply chains and interdicted network bandwidth in the Tactical Echelon.

Both circumstances emphasize the need to have maintenance capabilities at the point of need on the battlefield without the need for support reach back. This project will significantly facilitate these capabilities.

Description

The Artificial Intelligence and Model-Based Systems Engineering topic will improve the development, operation and sustainment of Test Program Sets for the maintenance of electronic components of weapon systems.

It has direct relevance to all weapon systems and end items across all Army commodities, ranging from ground, air, missile to Command, Control, Computers, Communications, Cyber Defense, Intelligence, Surveillance and Reconnaissance. Current TPS developments can take a year or more with costs ranging from over a million dollars per TPS. The Army needs over a thousand TPS for all types of weapon systems.

Phase I

The Army will only accept Phase I proposals for contracts worth up to $250,000 over a 6-month performance period.

  • Evaluation of TPS development prerequisite documentation: ATE specifications, ATE Model library and Unit Under Test technical data.
  • Development of UUT test strategy.
  • Evaluation and selection of suitable AI and apps for ATE/TPS/UUT model development & integration.
  • Evaluation and selection of AI optimization algorithms (e.g., ChatGPT+, Wolfram Alpha or equivalent).
  • Preliminary design of test program hardware and software using AI-based model development.

Phase II

TPS hardware and software prototype development, critical design, test, integration, verification, validation and acceptance (per TPS development procedures outlined in DA PAM 750-43).

Phase III

  • Sensor integration in mobile platforms with AI-assisted guided diagnostics.
  • PD TMDE, as the current leader of the Department of Defense ATS Management Board, which comprises Army, Navy, Air Force, Marines and other Joint Programs, will socialize the SBIR process with the other Services. The Navy, with a large TPS inventory and on-going development process, is interested in the digital engineering approach to TPS management.

Submission Information

All eligible businesses must submit proposals by noon, ET.

To view the full solicitation details, click here.

For more information, and to submit your full proposal package, visit the DSIP Portal.

Applied SBIR Help Desk: usarmy.pentagon.hqda-asa-alt.mbx.army-applied-sbir-program@army.mil

Helicopter

References:

Objective

This Army SBIR project will develop field-level maintenance and repair of weapon systems electronics that shorten supply chain latency for electronic component repairs. The solution must screen electronic components for no evidence of failure at the source in the tactical unit.

This mitigates the high cost of discovering NEOF at higher echelons of maintenance. The Army wants faster weapon system repairs, faster component turn-around-times, high equipment operational availability and high unit readiness at lower life-cycle costs.

The Army is transitioning to a warfighting doctrine of Multi-Domain Operations in Large Scale Combat Operations. This doctrine emphasizes the vulnerability of contested Logistics supply chains and interdicted network bandwidth in the Tactical Echelon.

Both circumstances emphasize the need to have maintenance capabilities at the point of need on the battlefield without the need for support reach back. This project will significantly facilitate these capabilities.

Description

The Artificial Intelligence and Model-Based Systems Engineering topic will improve the development, operation and sustainment of Test Program Sets for the maintenance of electronic components of weapon systems.

It has direct relevance to all weapon systems and end items across all Army commodities, ranging from ground, air, missile to Command, Control, Computers, Communications, Cyber Defense, Intelligence, Surveillance and Reconnaissance. Current TPS developments can take a year or more with costs ranging from over a million dollars per TPS. The Army needs over a thousand TPS for all types of weapon systems.

Phase I

The Army will only accept Phase I proposals for contracts worth up to $250,000 over a 6-month performance period.

  • Evaluation of TPS development prerequisite documentation: ATE specifications, ATE Model library and Unit Under Test technical data.
  • Development of UUT test strategy.
  • Evaluation and selection of suitable AI and apps for ATE/TPS/UUT model development & integration.
  • Evaluation and selection of AI optimization algorithms (e.g., ChatGPT+, Wolfram Alpha or equivalent).
  • Preliminary design of test program hardware and software using AI-based model development.

Phase II

TPS hardware and software prototype development, critical design, test, integration, verification, validation and acceptance (per TPS development procedures outlined in DA PAM 750-43).

Phase III

  • Sensor integration in mobile platforms with AI-assisted guided diagnostics.
  • PD TMDE, as the current leader of the Department of Defense ATS Management Board, which comprises Army, Navy, Air Force, Marines and other Joint Programs, will socialize the SBIR process with the other Services. The Navy, with a large TPS inventory and on-going development process, is interested in the digital engineering approach to TPS management.

Submission Information

All eligible businesses must submit proposals by noon, ET.

To view the full solicitation details, click here.

For more information, and to submit your full proposal package, visit the DSIP Portal.

Applied SBIR Help Desk: usarmy.pentagon.hqda-asa-alt.mbx.army-applied-sbir-program@army.mil

References:

Helicopter

AI-Enhanced TPS Development and Sustainment

Scroll to Top