To help ensure its brigade combat teams' (BCTs') readiness, the U.S. Army implemented the authorized stockage list, a carefully calculated list of the repair parts that each team should keep on hand. The introduction of common authorized stockage lists, which account for BCT type (armored, infantry, and Stryker), and the incorporation of a mathematical optimization approach, allow for higher ASL performance and better mission readiness support.
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Research Questions
- What are the advantages of pooling demand histories across BCTs of the same type — that is, switching to CASLs?
- What are the benefits of shifting from a two-step heuristic to a mathematical optimization formulation?
The operational effectiveness of the U.S. Army's brigade combat teams (BCTs) depends critically on their tactical and combat equipment being available and mission ready. When equipment breaks down, maintainers require repair parts to restore equipment availability. This can happen quickly if the parts are on hand in the BCT's own Supply Support Activity (SSA). When critical parts are not available in the SSA, repairs are delayed, and equipment remains unavailable for use in operations.
For over two decades, the Army has improved the methods used to calculate authorized stockage lists (ASLs) to capitalize on changes to its supply and maintenance information systems and to keep pace with advances in data collection and integration, inventory management metrics, and analytic methods. This article details the introduction of common ASLs (CASLs), single ASLs for each of the three BCT types (armored [ABCT], infantry [IBCT], and Stryker [SBCT]). The move to CASLs was enabled by pooling demand data across like BCTs and by shifting from a two-step heuristics approach to mathematical optimization. These changes provided higher ASL performance and thus better support of equipment readiness in high-tempo operations, SSA mobility on the battlefield, and reduced workload required to reconfigure storage locations and redistribute parts no longer authorized for stockage.
Key Findings
- Pooling demands across BCTs of the same type provides additional periods of high-intensity training events, better information on part demand variability, more data to determine a robust mix of low-demand parts, and a reduced likelihood that atypical part demands at one or two BCTs would drive ASL changes.
- Using a mathematical optimization approach allows the Army to stress the mission criticality of different types of equipment in the BCT, allows for storage constraints to ensure the CASLs are mobile, and allows the use of weighting factors to reduce the number of changes to the ASL and, hence, SSA workload and up-front inventory investment required for CASL updates.
- Varying weighting factors and storage capacity constraints enables rapid analyses of trade-offs across multiple dimensions (e.g., transition costs to update the CASL, storage configuration, mobility, and performance).
Table of Contents
Chapter One
Introduction
Chapter Two
Benefits of Shifting to CASLs
Chapter Three
The Mathematical Optimization Formulation
Chapter Four
Conversion of the Army's Armored, Infantry, and Stryker BCTs to CASLs
Chapter Five
Updates to the Common ASL
Research conducted by
The research described in this report was sponsored by the U.S. Army Materiel Command and U.S. Army Sustainment Command (ASC) and conducted by the Forces and Logistics Program within the RAND Arroyo Center.
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