Cited by 26Reliability and Maintenance OptimizationFault Detection and Control SystemsMachine Fault Diagnosis Techniques
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A predictive maintenance policy for manufacturing systems considering degradation of health monitoring device
Open accessDinh, Duc-Hanh, Do, Phuc, Hoang, Van-Thanh, Vo, Nhu-Thanh, Bang, Tao Quang·2024·Reliability Engineering & System Safety
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Crossref · 10.1016/j.ress.2024.110177
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In the citing paper
“The proposed method achieved an optimal maintenance cost rate; compared to the conventional method, which had a higher cost rate, it reduced costs by approximately 12.5%.”
From Impact of Sensor Degradation on Measurement Uncertainty in Prognostics and Maintenance Decision-Making: State of the art and challenges (2025) · cites this paper as Dinh et al. (2024)
In the citing paper
“Further analysis showed that the maintenance cost rate is sensitive to the sensor replacement threshold: compared to the optimal value, lower thresholds increase costs due to frequent sensor replacements, while higher thresholds reduce replacements but raise costs from system failures or poor maintenance timing caused by degraded sensor accuracy.”
From Impact of Sensor Degradation on Measurement Uncertainty in Prognostics and Maintenance Decision-Making: State of the art and challenges (2025) · cites this paper as Dinh et al. (2024)
In the citing paper
“Dinh et al. (2024) introduced an adaptive PdM strategy specifically designed for manufacturing systems where measurement uncertainty arises from the degradation of health monitoring devices (HMDs).”
From Impact of Sensor Degradation on Measurement Uncertainty in Prognostics and Maintenance Decision-Making: State of the art and challenges (2025) · cites this paper as Dinh et al. (2024)
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Research works printed but not linked: 33
- Ait Mokhtar, 2023, Imperfect maintenance modeling and assessment of repairable multi-component systems, Reliab Eng Syst Saf, 234, 10.1016/j.ress.2023.109189 · DOI
- Barker, 2009, Optimal non-periodic inspection for a multivariate degradation model, Reliab Eng Syst Saf, 94, 33, 10.1016/j.ress.2007.03.015 · DOI
- Bi, 2010, Advances in 3D data acquisition and processing for industrial applications, Robot Comput Integr Manuf, 26, 403, 10.1016/j.rcim.2010.03.003 · DOI
- Cinar, 2022, A predictive maintenance system design and implementation for intelligent manufacturing, Machines, 10, 1006, 10.3390/machines10111006 · DOI
- Dinh, 2022, Multi-level opportunistic predictive maintenance for multi-component systems with economic dependence and assembly/disassembly impacts, Reliab Eng Syst Saf, 217, 10.1016/j.ress.2021.108055 · DOI
- Elfring, 2021, Particle filters: a hands-on tutorial, Sensors, 21, 10.3390/s21020438 · DOI
- Fruth, S., Kruppa, S., & Schiffers, R. (2020). Condition monitoring for injection molding screws. 020023. 10.1063/5.0028341. · DOI
- González-Muñiz, 2022, Health indicator for machine condition monitoring built in the latent space of a deep autoencoder, Reliab Eng Syst Saf, 224, 10.1016/j.ress.2022.108482 · DOI
- Hachem, 2024, Different methods for RUL prediction considering sensor degradation, Reliab Eng Syst Saf, 243, 10.1016/j.ress.2023.109897 · DOI
- Han, 2021, Remaining useful life prediction and predictive maintenance strategies for multi-state manufacturing systems considering functional dependence, Reliab Eng Syst Saf, 210, 10.1016/j.ress.2021.107560 · DOI
- Hao, 2020, Condition-based maintenance with imperfect inspections for continuous degradation processes, Appl Math Model, 86, 311, 10.1016/j.apm.2020.05.013 · DOI
- Healy, 2008, Wireless sensor node hardware: a review, 2008 IEEE Sens, 621, 10.1109/ICSENS.2008.4716517 · DOI
- Huynh, 2012, Maintenance decision-making for systems operating under indirect condition monitoring: value of online information and impact of measurement uncertainty, IEEE Trans Reliab, 61, 410, 10.1109/TR.2012.2194174 · DOI · Paper page
- Huynh, 2019, A parametric predictive maintenance decision-making framework considering improved system health prognosis precision, IEEE Trans Reliab, 68, 375, 10.1109/TR.2018.2829771 · DOI
- Jimenez, 2020, Developing a predictive maintenance model for vessel machinery, J Ocean Eng Sci, 5, 358, 10.1016/j.joes.2020.03.003 · DOI
- Kyas, 2012, Measuring of temperature and pressure in injection mold, Int J Math Comput Simul, 6, 600
- Letot, 2015, A degradation model for maintenance improvement in respect of cost and availability, J Qual Maint Eng, 21, 55, 10.1108/JQME-01-2013-0001 · DOI
- Li, 2023, Implicit Kalman filtering method for remaining useful life prediction of rolling bearing with adaptive detection of degradation stage transition point, Reliab Eng Syst Saf, 235, 10.1016/j.ress.2023.109269 · DOI
- Liu, 2020, Stochastic filtering approach for condition-based maintenance considering sensor degradation, IEEE Trans Autom Sci Eng, 17, 177, 10.1109/TASE.2019.2918734 · DOI
- Liu, 2024, Optimal condition-based maintenance policy for leased equipment considering hybrid preventive maintenance and periodic inspection, Reliab Eng Syst Saf, 242, 10.1016/j.ress.2023.109724 · DOI
- Liu, 2021, Optimal multi-type inspection policy for systems with imperfect online monitoring, Reliab Eng Syst Saf, 207, 10.1016/j.ress.2020.107335 · DOI
- Ma, 2019, Structural damage detection considering sensor performance degradation and measurement noise effect, Measurement, 131, 431, 10.1016/j.measurement.2018.08.040 · DOI
- Ma'arif, 2020, Kalman filter for noise reducer on sensor readings, Signal Image Process Lett, 1, 11, 10.31763/simple.v1i2.2 · DOI
- Mukhopadhyay, 2023, Remaining lifetime of degrading systems continuously monitored by degrading sensors, Reliab Eng Syst Saf, 231, 10.1016/j.ress.2022.109022 · DOI
- Nguyen, 2019, Joint optimization of monitoring quality and replacement decisions in condition-based maintenance, Reliab Eng Syst Saf, 189, 177, 10.1016/j.ress.2019.04.034 · DOI
- Salehpour-Oskouei, 2017, Risk assessment of sensor failures in a condition monitoring process; degradation-based failure probability determination, Int J Syst Assur Eng Manag, 8, 584, 10.1007/s13198-017-0573-0 · DOI
- Wang, 2023, An inspection-based replacement planning in consideration of state-driven imperfect inspections, Reliab Eng Syst Saf, 232, 10.1016/j.ress.2022.109064 · DOI
- Wang, 2011, A model for residual life prediction based on Brownian motion with an adaptive drift, Microelectron Reliab, 51, 285, 10.1016/j.microrel.2010.09.013 · DOI
- Zhang, 2022, A condition-based maintenance policy considering failure dependence and imperfect inspection for a two-component system, Reliab Eng Syst Saf, 217, 10.1016/j.ress.2021.108069 · DOI
- Zhang, 2022, Domain adaptation mixture of gaussian processes for online soft sensor modeling of multimode processes when sensor degradation occurs, IEEE Trans Industr Inform, 18, 4654, 10.1109/TII.2021.3120509 · DOI
- Zhang, 2023, Gaussian mixture continuously adaptive regression for multimode processes soft sensing under time-varying virtual drift, J Process Control, 124, 1, 10.1016/j.jprocont.2023.02.003 · DOI
- Zhao, 2024, A condition-based inspection-maintenance policy for critical systems with an unreliable monitor system, Reliab Eng Syst Saf, 242, 10.1016/j.ress.2023.109710 · DOI
- Zhou, 2023, Hybrid system response model for condition monitoring of bearings under time-varying operating conditions, Reliab Eng Syst Saf, 239, 10.1016/j.ress.2023.109528 · DOI
Cited by
Sorted by citations
Thai, T.-T. N., Do, P., Iung, B., & Gardoni, P. (2025) · International Journal of Prognostics and Health Management · doi:10.36001/ijphm.2025.v16i4.4306 · Cited by 6
Self-citation
Metadata
- Authors
- Dinh, D.-H., Do, P., Hoang, V.-T., Vo, N.-T., & Bang, T. Q.
- Affiliations
- University of Da Nang (VN)
- Centre National de la Recherche Scientifique (FR)
- Corresponding author
- Dinh, Duc-Hanh
- Venue
- Reliability Engineering & System Safety
- Publisher
- Elsevier BV
- Published
- 2024-08
- Volume
- 248
- Pages
- 110177
- ISSN
- 0951-8320 (ISSN-L)
- OpenAlex
- W4396529063
- Cited by
- 26
- References
- 0
- Citations by year
- 2026: 16 · 2025: 9 · 2024: 1
- FWCI
- 6.75
- Type
- journal article
- Language
- en
- Open access
- green
- hal.science
- Licence
- Locations
- Reliability Engineering & System Safety (publishedVersion)
- HAL (submittedVersion, cc-by-nc)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Vingroup JSC
- Topics
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Reliability and Maintenance Optimization
- Physical Sciences › Engineering › Control and Systems Engineering › Fault Detection and Control Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Machine Fault Diagnosis Techniques
- Keywords
- predictive maintenance, manufacturing systems, condition monitoring, Kalman filter state estimation, maintenance decision-making, cost model, injection molding machine, data uncertainty
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