Generic Logistics R&D Technology Demonstrations

The Logistics Research and Development Technology (Log R&D) program, managed by the Defense Logistics Agency (DLA), is a key element of the Department of Defense's Research, Development, Test & Evaluation (RDT&E) budget. Its primary goal is to advance logistics capabilities for the military services, allied forces, and other federal agencies by developing and demonstrating innovative technologies and business processes.

The program is structured around three main Lines of Effort (LOEs): Logistics Operations Innovation, Predictive Analytics/Modeling & Simulation, and Smart Warehouse Modernization. These LOEs are closely aligned with the DLA Strategic Plan, which emphasizes digital business transformation, improved data transparency, and enhanced supply chain performance.

Logistics Operations Innovation (LOI) focuses on integrating advanced technologies and innovative processes into DLA's supply chains to improve warfighter readiness and weapons system sustainment. Key objectives include securing supply chains, developing renewable energy solutions, and implementing anti-counterfeiting measures. The LOI supports several portfolios such as efforts to investigate alternative fuels and fuel quality, and initiatives to modernize procurement processes through market intelligence and smart contracting using blockchain technology. Additionally, work is underway to enhance asset visibility and supplier illumination, especially in contested logistics environments.

Recent progress includes supporting research into woody biomass conversion to produce liquid hydrocarbon fuels and developing analytical methods for fuel quality and thermal stability. Efforts have piloted contract quality review dashboards and explored AI/ML solutions for acquisition challenges. Databases have been established to support Trade Agreement Act compliance, and large-scale testing of asset visibility technologies has been conducted in multiple geographic combatant commands. These activities are intended to improve material availability and shorten lead times for critical supplies.

Predictive Analytics, Modeling & Simulation (PAM) is centered on developing predictive analytic solutions using artificial intelligence and machine learning (AI/ML) to optimize business operations and inform decision-making. Projects have included developing cyber digital twins for operational technology security, piloting remote surveillance inspection using augmented/virtual reality, and implementing digital twin modeling for warehouse modernization. Future objectives involve integrating generative AI, large language models, and quantum computing to further enhance supply chain risk management and operational forecasting.

The Smart Warehouse Modernization (SWM) LOE is dedicated to transforming DLA's distribution and disposition operations through the adoption of interconnected, cyber-secure technologies and automation. Efforts include identifying and replacing legacy systems with innovative solutions, installing a 5G private network testbed, implementing augmented reality for warehouse processes, and conducting feasibility studies for automated inventory management. Planned initiatives involve further research into asset visibility, automation, network optimization, and circular economy practices to address high-risk issues identified by the Government Accountability Office.

DLA R&D utilizes flexible acquisition strategies such as Broad Agency Announcements (BAAs), Indefinite Delivery/Indefinite Quantity (IDIQ) contracts, and Other Transaction Authority (OTA) agreements. These approaches enable the agency to competitively source innovative solutions from industry and academia, including non-traditional contractors. The use of BAAs allows for a wide range of technical proposals, while OTAs facilitate rapid prototyping and transition to production. A contract vehicle is employed to acquire IT and R&D support services from pre-qualified performers, ensuring access to specialized expertise in logistics, engineering, and technology development.