When I initiated my research on Integrated Logistics Support (ILS), I anticipated complexity. I expected rigorous mathematical models and dense datasets. What I encountered was silence.
Searching for practical, engineering-grade ILS resources yielded plenty of high-level policy but almost zero operational methodology. To quantify this scarcity, I analyzed the academic output.
The 100:1 Asymmetry
For every 100 papers written on generic “Supply Chain Management”, there is barely 1 paper on “Integrated Logistics Support”.
While the commercial sector debates the nuances of AI and Blockchain, the defense support domain remains a ghost town. We are attempting to sustain 5th-generation platforms using foundational theories established decades before the digital era.
The “Missing Middle”
This creates a critical structural disconnect I define as the “Missing Middle”:
- The Top Layer: High-level guidebooks dealing with policy and acquisition strategy.
- The Bottom Layer: Complex XML schemas (S1000D/S3000L) and data exchange protocols.
- The Gap: The engineering layer where data is actually converted into readiness decisions.
The Fragmented Standard
Every attempt to solve a problem in this “Missing Middle” collides with reality. In theory, standards exist for every contingency. In practice, these standards often fail to account for the stochastic nature of field operations.
ILS is an engineering masterpiece, but currently, it resembles a 5,000-piece puzzle scattered on the floor. The components exist, but the connective architecture is missing.
Protocol Objectives
I am documenting the bridge I couldn’t find.
This is not a blog for general theories. It is an Engineering Log designed to connect “textbook principles” with “hangar reality”.
This repository will explore:
- Gap Analysis: Decoding where literature fails the engineer.
- Case Studies: Real-world readiness engineering.
- Translation: Converting complex standards into decision logic.
- Modernization: How Probabilistic Modeling and AI can finally modernize this field.