Grant: CCI Applied Research and Development Grants

Railways are an essential part of our local and global transport system. Railcar transport is known to be cost-effective, environmentally friendly, reliable, and energy efficient. This project will advance a solution which applies technology to automate the loading of railcars. RAYHAWK is a Saskatoon based company continuing the evolution of railcar transport by developing solutions for the autonomous loading and unloading of bulk cargo. RAYHAWK has recently completed their first customer installation of their solution for granular product railcar loading, have multiple patents, and are actively working to expand their capabilities. Currently, this initial solution is a mechatronic system tailored for a potash loadout facility, and supports variations of a single top loading railcar type. The key challenge to expanding their solution is to rapidly support a multitude of additional railcar types. In their initial development process, physical replicas of railcar tops were used for the machine learning required to train and validate the system performance. This research will augment physical replicas of railcar tops with digital replicas and behavioral models, or digital twins, that can be used to create a Virtual Training Platform, VTP. The VTP can be used to more efficiently and comprehensively train the system, and the physical replicas will still be required for real world performance validation. This research lays the foundation for future autonomous loading solutions requiring expanded railcar configurations, in both digital and physical form, for machine learning, training, and performance validation.