The DOI matches its Crossref record.
A Model for a Multi-Item, Multi-Echelon, Multi-Indenture Inventory System
Abstract
The purpose of this paper is to describe a mathematical model, called MOD-METRIC, for the control of a multi-item, multi-echelon, multi-indenture inventory-system for recoverable items, that is, items subject to repair when they fail. Discussion is limited to two-echelon multi-item systems in which an item may be demanded at any one of several locations called bases; in turn, these bases receive inventory from a central location called a depot. The objectives of the model are to describe the logistics relationship between an assembly and its subassemblies, and to compute spare stock levels for both echelons for the assembly and subassemblies with explicit consideration of this logistics relationship. In particular, the model is used to determine the base and depot spare stock levels which minimize total expected base backorders for the assembly subject to a system investment constraint. An example is given showing how the model can be used to calculate spare engine and engine module stock levels. MOD-METRIC has been implemented by the Air Force as the method for computing recoverable spare stock levels for the F-15 weapon system.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
A survey of maintenance models for multi-unit systems
Cho, D. I., & Parlar, M. (1991) · European Journal of Operational Research · doi:10.1016/0377-2217(91)90141-h · Cited by 678
Performance Contracting in After-Sales Service Supply Chains
Kim, S.-H., Cohen, M. A., & Netessine, S. (2007) · Management Science · doi:10.1287/mnsc.1070.0741 · Cited by 520
Metadata
- Authors
- Muckstadt, J. A.
- Venue
- Management Science
- Published
- 1973-12
- Volume
- 20
- Issue
- 4-part-i
- Pages
- 472-481
- ISSN
- 0025-1909 (ISSN-L)
- 1526-5501
- OpenAlex
- W2105657500
- Cited by
- 341
- References
- 0
- FWCI
- 1.24
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A Model for a Multi-Item, Multi-Echelon, Multi-Indenture Inventory System. https://app.cochat.ai/papers/10.1287/mnsc.20.4.472
- The paper
- Muckstadt, J. A. (1973). A Model for a Multi-Item, Multi-Echelon, Multi-Indenture Inventory System. Management Science. https://doi.org/10.1287/mnsc.20.4.472
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
