Modeling the Residual Useful Life of Bearing Grease

University  The University of Texas Rio Grande Valley (UTRGV)
Principal Investigators  Doug Timmer, Ph.D., Manufacturing Engineering (PI)
Robert Jones, Ph.D., Mechanical Engineering (Co-PI)
Constantine Tarawneh, Ph.D., Mechanical Engineering (Co-PI)
PI Contact Information  Manufacturing Engineering
ENGR 3.258
Dept. (956) 665-2606
Office (956) 665-2608 
Funding Source(s) and Amounts Provided (by each agency or organization)  Federal Funds (USDOT UTC Program): $54,351
Cost Share Funds (UTRGV): $10,977
Total Project Cost  $65,328
Agency ID or Contract Number  DTRT13-G-UTC59
Start and End Dates November 2013 — December 2014
Brief Description of Research Project  This research developed analytical models to predict the residual useful life of bearing grease. Modeling techniques employed include mechanistic or first principle models based upon process kinetics and empirical models including physics-based reliability models, non-linear regression and neural networks. The analytical models provide users the ability to predict residual life based upon operational characteristics.
Keywords analytical model, residual life, bearing grease, accelerated life testing, neural networks, nonlinear regression, oxidation induction time
Describe Implementation of Research Outcomes (or why not implemented) Place Any Photos Here A linear regression model was developed based on a split, split-plot design to predict residual life of grease based upon operational characteristics. Some of the outcomes are listed hereafter: Characterized residual life of bearing grease as the Oxidation Induction Time (OIT). Novel utilization of statistical design of experiments and linear regression to model residual life of bearing grease. The data was collected as a split, split-plot design and analyzed using restricted maximum likelihood technique implemented in MATLAB. Mathematical model that predicts residual life of bearing grease. The following findings were established: (a) the mileage had the most significant impact upon the life of the bearing grease and the relationship was negative, (b) the bearing temperature had the second largest impact upon bearing grease and the correlation between temperature and OIT was negative, and (c) OIT values were higher, indicating larger remaining life, for the grease samples at the spacer ring location than grease sampled at the inner and outer bearing raceway.
Impacts/Benefits of Implementation (actual, not anticipated) The research performed for this project has resulted in two national conference papers and presentations, and a Master’s Thesis. The following are benefits resulting from this research:

1. Timmer, D., Martinez, T., Jones, R., and Tarawneh, C., "Modeling the Useful Life of Railroad Bearing Grease," 2014 Informs Conference, San Francisco, CA, November 9-12, 2014.

2. Martinez, T., Timmer, D., Jones, R., and Tarawneh, C., "Developing Empirical Models of Railroad Bearing Grease," Proceedings of the ASME 2015 Joint Rail Conference, San Jose, CA, March 23-26, 2015.

3. Martinez, T., “Modeling the Residual Useful Life of Bearing Grease,” Master’s Thesis, The University of Texas Rio Grande Valley, December 2015. [Link to PDF (1.6 MB)]
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