Improving Logistics Processes (formerly Logistics Process)

Abstract

The Improving Logistics Processes (ILP) Strategic Focus Area (SFA) encompasses R&D efforts within the Logistics Technology Research program, formerly Weapon System Sustainment (WSS), and the Acquisition Modernization Technology Research (AMTR) program to support DLA business functional units through applied research and development of advanced technologies to improve business processes and operational methods, leverage the application of leading edge logistics “out-of-the box” concepts using disruptive technology business tools, and support DLA’s technological transformation effort. To qualify for R&D funding, the R&D effort must develop and apply technology and processes over and above current baseline IT systems and continuous improvements efforts. Although all DLA processes are in scope, the strategic focus for this budget cycle is in Procurement, Planning, Technical Quality and the Major Subordinate Commands. Innovative process changes and new technologies will be researched in these areas to drive improvements to internal costs, reduce award delays, and improve material availability, supply chain security, demand forecasting and logistical planning. This will be accomplished through the use of Artificial Intelligence/Machine Learning (AI/ML), blockchain technology, and research of emerging commercial best practices and technologies. *In FY 2023, this SFA, Improving Logistics Processes (GLTD), closes out. The LTR program shifts to the Predictive Analytics / Modeling & Simulation (PAM) Line of Effort (see R-2A) and the AMTR program shifts to the Logistics Operations Innovation (LOI) Line of Effort (see R-2A).

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Document Details

Document Type
Project
Publication Date
Oct 01, 2024
Source ID
GLTD_0603712S_3_0400_PB_2024

Tags

Readers

  • Logistics and Supply Chain Management.
  • Military Science and Technology Research and Modernization.
  • Organizational Process Management (OPM).

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy

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