DLA AI-Driven Manufacturing Capacity Visibility System

Award Maximum: $100,000 Period of Performance: 6 months Phase Type: Phase I

OBJECTIVE: The objective of this SBIR is to develop and prototype a secure, AI-driven system that provides DLA with real-time visibility into untapped manufacturing capabilities and capacities from tertiary sources like educational and research institutions. The final system should be able to map these resources to specific defense-related manufacturing demands and facilitate their rapid and secure engagement.

DESCRIPTION: DLA needs to quickly find and use extra manufacturing capacity from places like universities and research labs, especially during national emergencies or when demand for military parts suddenly increases. Currently, there is no easy way to know what machines, skills, or production time are available at these facilities, or to securely and quickly bring them into the defense supply chain. This project aims to create a centralized, secure data system that provides real-time visibility into this untapped manufacturing power, allowing DLA to rapidly match available resources to critical defense needs, reducing risk and increasing the agility of the U.S. industrial base.

PHASE I: Not to exceed a duration of 6 months and a cost of $100,000.

Phase I: Proof of Concept

The goal of Phase I is to conduct a feasibility study that proves the core concepts of the proposed system are viable. This must be accomplished within 12 months for a cost not to exceed $100,000.

Phase I Deliverables:

A detailed report identifying and documenting available tertiary manufacturing capabilities from a representative sample of educational and research institutions.

A document defining the proposed secure protocols for real-time data exchange and a report on their feasibility.

A template legal framework, including a sample Non-Disclosure Agreement (NDA), designed to facilitate data sharing between institutions and the DoW.

A preliminary, proof-of-concept demand-mapping system that demonstrates the ability to correlate available capabilities with defense manufacturing needs.

A comprehensive Phase II development plan detailing the technical milestones, performance goals, and resource requirements for building the full prototype.

PHASE II: Not to exceed a duration of 24 months and a cost of $1,000,000.

Phase II: Prototype Development

The objective of Phase II is to develop, test, and demonstrate a functional prototype of the system in a relevant environment.

Phase II Deliverables:

A functional prototype of the manufacturing capacity database and mapping system, developed and demonstrated within the DLA J68 ARTET environment.

A final report detailing the results from real-world scenario testing with academic and institutional partners, validating the system's functionality, security, and efficiency.

Test data demonstrating that the prototype can successfully receive continuous data updates, map capacity to demand, and operate under the developed security protocols.

A validated and refined set of data management and advanced cybersecurity protocols that meet DoW compliance standards.

A detailed Phase III commercialization and transition plan outlining the strategy for full-scale implementation within DLA and potential expansion to other government and commercial markets.

PHASE III DUAL USE APPLICATIONS: A successful project has a direct path to a follow-on Phase III award with the DLA to transition the technology into a fully operational system.

Beyond its immediate use within DLA, this system is a foundational technology for a Civil Reserve Manufacturing Network. It would provide the necessary infrastructure for identifying, vetting, and mobilizing civilian industrial capabilities in response to national emergencies or defense surge requirements.

Furthermore, the developed system has significant commercial potential outside of government applications. It could be adapted to enhance manufacturing resource management and supply chain security in various industries, including automotive, aerospace, and consumer electronics, which face similar challenges in managing distributed manufacturing capacities and require greater supply chain resilience.