Expeditionary Advanced Base Operations (EABO) | Shipcom SiF Sustainment Decision Support Application

Background

Expeditionary Advanced Base Operations (EABO) is integral to the future direction of the USMC. The ability to sustain the Marine Corps stand-in forces SiF in a contested and dynamic environment is critical to the EABO Mission.

The current logistics environment does not support the USMC FD2030 initiative. Summary of the current challenges are:

  • Poor visibility of the logistics enterprise
  • Supply chains built strictly for efficiency not resiliency
  • Sustainment systems and nodes not compatible with Joint Logistics Enterprise (JLEnt) capabilities
  • Dependence on fixed site distribution nodes

Marine Corps Leadership recognizes that:

“Logistics is the Marine Corps current pacing function and the logistics enterprise is not constructed for the operational concepts now being developed in support of great power competition.”

Shipcom SiF Sustainment Decision Support Solution Objectives

The Shipcom Sustainment Decision Support Solution uses Artificial Intelligence and Machine Learning to target the following objectives:

Enabling global logistics awareness

  • Better situational awareness
  • Better access to a smarter JLEnt supply web
  • More productive and informed decision making

Diversifying distribution

  • Faster more resilient logistics response for delivery
  • Dynamically acquires, tracks and expedites material shipments

Improving sustainment

  • Provide forward sustainment to support and enable the joint force, and partners and allies

Operationalizing installations to support sustained operations

  • Aligns bases and stations as information network nodes, elements of the supply chain, and operating locations from which to fight
These objectives are used in design of the SiF Sustainment Decision Support Solution to provide transformational improvements to the current supply chain process. The figure below shows how.
AI Infused Supply Chain Process Flow

Our EABO Command and Control application demonstrates USMC FD2030 capabilities in the following areas:

Decision Support
AI-Infused Demand Fulfillment
SiF Sustainment Command Center

Shipcom SiF Sustainment Decision Support uses a modern, cutting-edge software platform with a powerful Artificial Intelligence Engine that enables users to make smarter decisions backed by data, analytics, forecasting and simulation. Shipcom is currently providing a pathway to Digital Transformation for the Navy, Air Force, Army, and Marine Corps. To maintain our military advantage in a digitally competitive world, the Department of Defense (DoD) must embrace AI technologies to improve fleet, joint force, and coalition situational awareness in contested areas to support friendly decision-making across the competition continuum.

The following shows features and benefits of Shipcom’s SiF Sustainment Solution:

Shipcom SiF C2 Capabilities
USMC SiF Benefit
AI infused JLEnt logistics web fulfilment
True Joint Force FAD/UND providing better allocation of critical resources and material
Integrated Global Pre-positioned Network (GPN)s
Faster more resilient logistics response for delivery
Integrated Combat Logistics Fleet
More effective stand-in sustainment
Dynamic Re-tasking (Distribution on the Move)
More productive and informed decision making
Condition Based Maintenance +
Better equipment readiness/maintenance effectiveness
Forward/distributed Defense Logistics Agency (DLA/NAVSUP)
Better access to a smarter JLEnt logistics web
JLEnt logistics web Interoperability
Provides collaboration between JLEnt logistics web stakeholders
Distributed Additive Manufacturing
Increased Mission Operational effectiveness
Zero Trust Security
Better Operational security & access
AI infused Business Intelligence
Improved Reporting speed and accuracy
Near Real-time Operational Awareness
Alignment to USMC FD 2030

Results

Includes primary use cases defined by USMC SMEs

Deployed/Prototype examples demonstration upon request

Rapid deployment of discrete capabilities using
Shipcom’s 90 Day Sprint Methodology

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