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  2020 (6)
Data-driven Adaptive Thresholding Model for Real-time Valve Delay Estimation in Digital Pump/Motors. Chehade, A.; Breidi, F.; Pate, K., S.; and Lumkes, J. International Journal of Fluid Power, 20(3): 271–294. 3 2020.
Data-driven Adaptive Thresholding Model for Real-time Valve Delay Estimation in Digital Pump/Motors [link]Website   bibtex   abstract
BLNN: An R package for training neural networks using Bayesian inference. Sharaf, T.; Williams, T.; Chehade, A.; and Pokhrel, K. SoftwareX, 11: 100432. 1 2020.
BLNN: An R package for training neural networks using Bayesian inference [link]Website   bibtex
Accelerating the Discovery of New DP Steel Using Machine Learning-Based Multiscale Materials Simulations. Chehade, A., A.; Belgasam, T., M.; Ayoub, G.; and Zbib, H., M. Metallurgical and Materials Transactions A. 4 2020.
Accelerating the Discovery of New DP Steel Using Machine Learning-Based Multiscale Materials Simulations [link]Website   bibtex
A Collaborative Gaussian Process Regression Model for Transfer Learning of Capacity Trends between Li-ion Battery Cells. Chehade, A.; and Hussein, A. IEEE Transactions on Vehicular Technology,1-1. 2020.
A Collaborative Gaussian Process Regression Model for Transfer Learning of Capacity Trends between Li-ion Battery Cells [link]Website   bibtex
Robust Artificial Neural Network-Based Models for Accurate Surface Temperature Estimation of Batteries. Hussein, A., A.; and Chehade, A. IEEE Transactions on Industry Applications,1-1. 2020.
Robust Artificial Neural Network-Based Models for Accurate Surface Temperature Estimation of Batteries [link]Website   bibtex
Power–Law Nonhomogeneous Poisson Process with a Mixture of Latent Common Shape Parameters. Chehade, A.; Shi, Z.; and Krivtsov, V. Reliability Engineering & System Safety,107097. 6 2020.
Power–Law Nonhomogeneous Poisson Process with a Mixture of Latent Common Shape Parameters [link]Website   bibtex
  2019 (6)
Structural Degradation Modeling Framework for Sparse Data Sets With an Application on Alzheimer’s Disease. Chehade, A.; and Liu, K. IEEE Transactions on Automation Science and Engineering, 16(1): 192-205. 1 2019.
Structural Degradation Modeling Framework for Sparse Data Sets With an Application on Alzheimer’s Disease [link]Website   bibtex
Sensor Fusion via Statistical Hypothesis Testing for Prognosis and Degradation Analysis. Chehade, A.; and Shi, Z. IEEE Transactions on Automation Science and Engineering,1-14. 2019.
Sensor Fusion via Statistical Hypothesis Testing for Prognosis and Degradation Analysis [link]Website   bibtex
Latent Function Decomposition for Forecasting Li-ion Battery Cells Capacity: A Multi-Output Convolved Gaussian Process Approach. Chehade, A., A.; and Hussein, A., A. . 7 2019.
Latent Function Decomposition for Forecasting Li-ion Battery Cells Capacity: A Multi-Output Convolved Gaussian Process Approach [link]Website   bibtex   abstract
A Multi-Output Convolved Gaussian Process Model for Capacity Estimation of Electric Vehicle Li-ion Battery Cells. Chehade, A., A.; and Hussein, A., A. 2019 IEEE Transportation Electrification Conference and Expo (ITEC),1-4. 6 2019.
A Multi-Output Convolved Gaussian Process Model for Capacity Estimation of Electric Vehicle Li-ion Battery Cells [link]Website   bibtex
The Sparse Reverse of Principal Component Analysis for Fast Low-Rank Matrix Completion. Chehade, A.; and Shi, Z. . 10 2019.
The Sparse Reverse of Principal Component Analysis for Fast Low-Rank Matrix Completion [pdf]Paper   The Sparse Reverse of Principal Component Analysis for Fast Low-Rank Matrix Completion [link]Website   bibtex   abstract
Monitoring Digital Technologies in Hydraulic Systems Using CUSUM Control Charts. Breidi, F.; Chehade, A.; and Lumkes, J. In ASME/BATH 2019 Symposium on Fluid Power and Motion Control, 10 2019. American Society of Mechanical Engineers
Monitoring Digital Technologies in Hydraulic Systems Using CUSUM Control Charts [link]Website   bibtex
  2018 (2)
A data-level fusion approach for degradation modeling and prognostic analysis under multiple failure modes. Chehade, A.; Song, C.; Liu, K.; Saxena, A.; and Zhang, X. Journal of Quality Technology, 50(2): 150-165. 4 2018.
A data-level fusion approach for degradation modeling and prognostic analysis under multiple failure modes [link]Website   bibtex
Design of a Transparent Hydraulic/Pneumatic Excavator Arm for Teaching and Outreach Activities. Pate, K.; Marx, J.; Chehade, A.; and Breidi, F. In 2018 ASEE Annual Conference & Exposition, 6 2018.
Design of a Transparent Hydraulic/Pneumatic Excavator Arm for Teaching and Outreach Activities [link]Website   bibtex
  2017 (3)
Optimize the Signal Quality of the Composite Health Index via Data Fusion for Degradation Modeling and Prognostic Analysis. Liu, K.; Chehade, A.; and Song, C. IEEE Transactions on Automation Science and Engineering, 14(3): 1504-1514. 7 2017.
Optimize the Signal Quality of the Composite Health Index via Data Fusion for Degradation Modeling and Prognostic Analysis [link]Website   bibtex
Sensory-Based Failure Threshold Estimation for Remaining Useful Life Prediction. Chehade, A.; Bonk, S.; and Liu, K. IEEE Transactions on Reliability, 66(3): 939-949. 9 2017.
Sensory-Based Failure Threshold Estimation for Remaining Useful Life Prediction [link]Website   bibtex
Data-driven Approaches for Condition Monitoring and Predictive Analytics. Chehade, A. Ph.D. Thesis, 2017.
bibtex
  2014 (2)
Optimal dynamic behavior of adaptive WIP regulation with multiple modes of capacity adjustment. Chehade, A.; and Duffie, N. In Procedia CIRP, volume 19, pages 168-173, 2014. Elsevier
bibtex   abstract
Control theoretical modeling of transient behavior of production planning and control: A review. Duffie, N.; Chehade, A.; and Athavale, A. In Procedia CIRP, volume 17, pages 20-25, 2014. Elsevier
bibtex   abstract
  2012 (1)
Dynamics of autonomously acting products and work systems in production and assembly. Jeken, O.; Duffie, N.; Windt, K.; Blunck, H.; Chehade, A.; and Rekersbrink, H. CIRP Journal of Manufacturing Science and Technology, 5(4): 267-275. 2012.
bibtex   abstract