An Empirical Approach to Estimate the Reliability of LEDs as Components of Military Equipment
DOI:
https://doi.org/10.3849/aimt.02054Keywords:
military equipment, LED, accelerated testing, reliability estimation, lifetime estimation, survival function, cumulative hazard functionAbstract
Military equipment is highly specialized and integrates advanced technologies to operate reliably in complex environments. Light-emitting diodes (LEDs) are increasingly used in military systems due to their superior performance, long lifetime, and high reliability, making their reliability critical to overall system effectiveness and combat capability. This study proposes an empirical framework for estimating LED reliability using accelerated reliability testing combined with statistical analysis, explicitly linking test conditions to actual operating conditions. The methodology follows a structured, stepwise procedure encompassing test design, data acquisition, and reliability estimation. It is applied to LEDs subjected to frequent ON/OFF cycling, yielding robust estimates of the lifetime distribution, survival function, and cumulative hazard function.
References
MIL-STD-810H:2019, Department of Defense Test Method Standard: Envi-ronmental Engineering Considerations and Laboratory Tests.
MIL-STD-883L:2019, Department of Defense Test Method Standard for Micro-circuits.
MIL-STD-785B:1980, Military Standard: Reliability Program for Systems and Equipment Development and Production.
MIL-STD-781A:1996, Military Handbook: Reliability Test Methods, Plans, and Environments for Engineering Development, Qualification, and Produc-tion.
IEC 60300:2023, Dependability Management.
MIL-HDBK-217F:1991, Military Standard: Reliability Prediction of Electronic Equipment.
IEEE 1413:2010, IEEE Standard Framework for Reliability Prediction of Hardware.
O’CONNOR, P. and A. KLEYNER. Practical Reliability Engineering. 5th ed. New York: Wiley, 2012. ISBN 1-119-96126-2.
CU, X.P. and H.A. BUI. Methodologies for Reliability Prediction of Electronic Component in Military Vehicles. Advances in Military Technology, 2019, 14(1), pp. 89-98. https://doi.org/10.3849/aimt.01276.
KYATAM, S., L.N. ALVES, S. MASLOVSKI and J.C. MENDES. Impact of Die Carrier on Reliability of Power LEDs. Journal of the Electron Devices So-ciety, 2021, 9, pp. 854-863. https://doi.org/10.1109/JEDS.2021.3115027.
TSAI, Y.C., J.P. LEBURTON and C. BAYRAM. Quenching of the Efficiency Droop in Cubic Phase InGaAlN Light-Emitting Diodes. IEEE Transactions on Electron Devices, 2022, 69(6), pp. 3240-3245. https://doi.org/10.1109/TED.2022.3167645.
NELSON, W.B. Accelerated Testing: Statistical Models, Test Plans, and Data Analysis. New York: Wiley, 2009. ISBN 978-0-4703-1679-5.
IEC 62506:2023, Methods for Product Accelerated Testing.
IES LM-80-08:2008, Approved Method: Measuring Lumen Maintenance of LED Light Sources.
IES TM-21-11:2011, Projecting Long-Term Lumen Maintenance of LED Light Sources.
LIMON, S., O.P. YADAV and H. LIAO. A Literature Review on Planning and Analysis of Accelerated Testing for Reliability Assessment. Quality and Relia-bility Engineering International, 2017, 33(8), pp. 2361-2383. https://doi.org/10.1002/qre.2195.
Accelerated Life Testing Data Analysis Reference [online]. Tucson: ReliaSoft, 2024 [viewed 2025-10-10]. Available from: https://help.reliasoft.com/reference/accelerated_life_testing_data_analysis/pdfs/alt_ref.pdf
HERZOG, A., et al. Long-Term Temperature-Dependent Degradation of 175 W Chip-on-Board LED Modules. IEEE Transactions on Electron Devices, 2022, 69(12), pp. 6830-6836. https://doi.org/10.1109/TED.2022.3214169.
SINGH, P. and C. TAN. Degradation Physics of High Power LEDs in Outdoor Environment and the Role of Phosphor in the Degradation Process. Scientific Reports, 2016, 6, 24052. https://doi.org/10.1038/srep24052.
TRUONG, M.T., P. DO, L. MENDIZABAL and B. IUNG. An Improved Accel-erated Degradation Model for Led Reliability Assessment with Self-Heating Impacts. Microelectronics Reliability. 2022, 128, 114428. https://doi.org/10.1016/j.microrel.2021.114428.
CHOI, H., L. WANG, S.W. KANG, J. LIM and J. CHOI. Precise Measurement of Junction Temperature by Thermal Analysis of Light-Emitting Diode Operat-ed at High Environmental Temperature. Microelectronics Reliability, 2021, 235, 111451. https://doi.org/10.1016/j.mee.2020.111451.
IBRAHIM, M.S., J. FAN, W.K. YUNG, Z. JING, X. FAN, W. VAN DRIEL and G. ZHANG. System Level Reliability Assessment for High Power Light-Emitting Diode Lamp Based on a Bayesian Network Method. Measurement, 2021, 176, 109191. https://doi.org/10.1016/j.measurement.2021.109191.
VALIŠ, D., M. FORBELSKÁ, Z. VINTR, Q.T. LA and J. LEUCHTER. Per-spective Estimation of Light Emitting Diode Reliability Measures Based on Multiply Accelerated Long Run Stress Testing Backed Up by Stochastic Diffu-sion Process. Measurement, 2023, 206, 112222. https://doi.org/10.1016/j.measurement.2022.112222.
DO, G.H., S.J. LEE, J.S. KIM and J.Y. KIM. Development of Accelerated Life Testing Apparatus for Light-Emitting Diode Therapy. IEEE Transactions on Device and Materials Reliability, 2021, 21(4), pp. 608-612. https://doi.org/10.1109/TDMR.2021.3121387.
WANG, Y., et al. Gamma-Irradiation-Accelerated Degradation in AlGaN-Based UVC LEDs Under Electrical Stress. IEEE Transactions on Nuclear Science, 2021, 68(2), pp. 149-155. https://doi.org/10.1109/TNS.2020.3046255.
TAN, K.Z., S.K. LEE and H.C. LOW. LED Lifetime Prediction Under Thermal-Electrical Stress. IEEE Transactions on Device and Materials Reliability, 2021, 21(3), pp. 310-319. https://doi.org/10.1109/TDMR.2021.3085579.
ENAYATI, J., A. RAHIMNEJAD and S.A. GADSDEN. LED Reliability As-sessment Using a Novel Monte Carlo-Based Algorithm. IEEE Transactions on Device and Materials Reliability, 2021, 21(3), pp. 338-347. https://doi.org/10.1109/TDMR.2021.3095244.
HOANG, A.D., Z. VINTR, D. VALIS and D. MAZURKIEWICZ. An Approach in Determining the Critical Level of Degradation Based on Results of Accelerat-ed Test. Eksploatacja i Niezawodność – Maintenance and Reliability, 2022, 24(2), pp. 330-337. https://doi.org/10.17531/ein.2022.2.14.
LETSON, B.C., S. BARKE, P. WASS, G. MUELLER, F. REN, S.J. PEARTON and J.W. CONKLIN. Deep UV AlGaN LED Reliability for Long Duration Space Missions. Journal of Vacuum Science & Technology A, 2023, 41(1), 013202. https://doi.org/10.1116/6.0002199.
CHEN, Y.C. A Tutorial on Kernel Density Estimation and Recent Advances. Biostatistics & Epidemiology, 2017, 1(1), pp. 161-187. https://doi.org/10.1080/24709360.2017.1396742.
SILVERMAN B.W. Density Estimation: for Statistics and Data Analysis. Lon-don: Chapman and Hall, 1986. ISBN 978-1-3151-4091-9.
COLOSIMO, E., F.V. FERREIRA, M. OLIVEIRA and C. SOUSA. Empirical Comparisons Between Kaplan-Meier and Nelson-Aalen Survival Function Es-timators. Journal of Statistical Computation and Simulation, 2022, 72(4), pp. 299-308. https://doi.org/10.1080/00949650212847.
VALIŠ, D., M. FORBELSKÁ, Z. VINTR, Q.T. LA and Z. KOHL. Light Emit-ting Diode Degradation and Failure Occurrence Modelling Based on Accelerat-ed Life Test. Engineering Failure Analysis, 2025, 169, 109200. https://doi.org/10.1016/j.engfailanal.2024.109200.
DARLING, D.A. and T.W. ANDERSON. Asymptotic Theory of Certain Good-ness-of-Fit Criteria Based on Stochastic Processes. The Annals of Mathematical Statistics, 1952, 23(2), pp. 193-212. https://doi.org/10.1214/aoms/1177729437.
Specification for Approval for LED GT-P10WW339910700. China: ShenZen GeTian Optoelectronics Co., 2013.
JCGM 100:2008, Evaluation of Measurement Data: Guide to the Expression of Uncertainty in Measurement.
34980A Data Acquisition System [online]. 2019 [viewed 2025-11-12]. Availa-ble from: https://www.keysight.com/zz/en/assets/7018-01247/data-sheets/5989-1437.pdf
SAINANI, K.L. Dealing with Non-Normal Data. Physical Medicine and Reha-bilitation, 2012, 4(12), pp. 1001-1005. https://doi.org/10.1016/j.pmrj.2012.10.013.
MOLUGARAM, K. and G.S. RAO. Analysis of Time Series. In: Statistical Techniques for Transportation Engineering. Oxford: Butterworth-Heinemann, 2017, pp. 463-489. https://doi.org/10.1016/B978-0-12-811555-8.00012-X.
REN, K., M. ALAM, P.P. NIELSEN, M. GUSSMANN and L. RÖNNEGÅRD. Interpolation Methods to Improve Data Quality of Indoor Positioning Data for Dairy Cattle. Frontiers in Animal Science, 2022, 3, 896666. https://doi.org/10.3389/fanim.2022.896666.
Downloads
Published
Issue
Section
Categories
License
Copyright (c) 2026 Advances in Military Technology
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors who publish with this journal agree to the following terms:
1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
Users can use, reuse and build upon the material published in the journal for any purpose, even commercially.
