Optimal Designs and Inspection Time Decisions for Gamma Accelerated Degradation Tests

ABSTRACT This study analytically derives optimal designs for gamma accelerated degradation tests while incorporating inspection time as a design variable under both D‐ and V‐optimality criteria. Under D‐optimality, we prove that the optimal design allocates test units exclusively to the lowest and highest stress levels and adopts the longest inspection interval, resulting in only two test groups. In contrast, under V‐optimality, although test units are also allocated to the lowest and highest stress levels, the optimal inspection intervals may differ within the same stress level depending on the underlying model parameters, resulting in either two or three test groups. These results can also be applied to the optimal design for gamma‐accelerated destructive degradation tests. We further compared our proposed design with conventional V‐optimal designs that assume equal inspection intervals across all stress levels. The results demonstrate that conventional V‐optimal designs may result in a significant loss of efficiency. Two illustrative examples, an accelerated destructive degradation test and an accelerated degradation test, are provided to demonstrate the practical implementation of the proposed methods and their effectiveness in improving estimation accuracy. Finally, a sensitivity analysis demonstrates that the proposed optimal designs are more robust than the conventional V‐optimal design.

Authors

Institutions

Publication Details

Journal
Naval Research Logistics (NRL)
Published
2026-06-17
DOI
https://doi.org/10.1002/nav.70083
Primary Topic
Reliability and Maintenance Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimal Designs and Inspection Time Decisions for Gamma Accelerated Degradation Tests

Hung‐Ping Tung, I‐Chen Lee
Naval Research Logistics (NRL)
Reliability and Maintenance Optimization
article

Optimal Designs and Inspection Time Decisions for Gamma Accelerated Degradation Tests

Hung‐Ping Tung, I‐Chen Lee
article en

Abstract

ABSTRACT This study analytically derives optimal designs for gamma accelerated degradation tests while incorporating inspection time as a design variable under both D‐ and V‐optimality criteria. Under D‐optimality, we prove that the optimal design allocates test units exclusively to the lowest and highest stress levels and adopts the longest inspection interval, resulting in only two test groups. In contrast, under V‐optimality, although test units are also allocated to the lowest and highest stress levels, the optimal inspection intervals may differ within the same stress level depending on the underlying model parameters, resulting in either two or three test groups. These results can also be applied to the optimal design for gamma‐accelerated destructive degradation tests. We further compared our proposed design with conventional V‐optimal designs that assume equal inspection intervals across all stress levels. The results demonstrate that conventional V‐optimal designs may result in a significant loss of efficiency. Two illustrative examples, an accelerated destructive degradation test and an accelerated degradation test, are provided to demonstrate the practical implementation of the proposed methods and their effectiveness in improving estimation accuracy. Finally, a sensitivity analysis demonstrates that the proposed optimal designs are more robust than the conventional V‐optimal design.

Naval Research Logistics (NRL)
National Yang Ming Chiao Tung University (TW), National Cheng Kung University (TW)
Openalex Percentile: Top 7%
Reliability and Maintenance Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.