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Design and analysis of experiments assessing handheld RFID readers in complex environments
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PRE
AI
J
Justin Strait*B
Brian WeaverM
Mary Frances DornB
Brendon A. ParsonsA
Alessandro Cattaneo DOI：10.1080/00224065.2026.2639400.png)
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Abstract
En 中文
Commercial Radio Frequency Identification (RFID) inventory tracking systems have been successfully deployed in numerous industries, but their viability for complex nuclear material environments is less understood. Success of RFID in this space requires thorough examination of factors which influence its ability to inventory random collections of objects, without much prior knowledge about the objects’ properties. In this work, we design and analyze experiments to identify relevant handheld RFID settings which optimize performance for one such challenging scenario, a typical cluttered shelf configuration comprised of numerous metal containers. We specify a full factorial split-plot design, and model the probability of a successful match for each container through a hierarchical generalized linear mixed model. The model is used to infer factors which maximize match probabilities for individual containers and the full configuration, and examine sensitivity of performance to these factors. Crucially, we model match probabilities without explicitly accounting for specific covariates about the containers themselves, in order to mimic practical scenarios in which information about objects being inventoried by RFID is unavailable.
Keywords:
Bayesian inference
experimental design
generalized linear mixed models
overdispersed count data
Journal
IF:
2.2
Papers:
57
Citations:
2.9K
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