Over the past seven years, MxV Rail has collaborated with a Class I railroad to analyze tie conditions and degradation based on machine vision data collected from various subdivisions across multiple geographical and operational locations. A tie rating system embedded in the inspection system determines whether a tie needs to be replaced. Both data and predictive analytics are used to assess the condition changes that can predict wood tie life and assist railroads in optimizing their maintenance and capital planning. The results show a reasonable correlation between wood tie life and the key factors affecting wood tie conditions, indicating the benefits of the machine vision-based tie inspection system. Nevertheless, some challenges identified during the analysis are also discussed in this Technology Digest.  Introduction  Due to the effects of mechanical load (e.g., tie splitting, plate cutting) and the decay associated with weathering, wood ties can degrade over time and perform their…