Optimize Service, Minimize Costs & Meet Projected Growth
Burlington Northern Santa Fe (BNSF) Railway, headquartered in Fort Worth, Texas, is one of seven North American Class I railroads and the second largest freight railroad network in North America.
BNSF wanted to optimize train service plans across the TransCon corridor, minimizing operating and infrastructure capital investment costs, to meet the projected traffic growth and fuel increases over the next five to ten years.
A number of model requirements included an accurate estimate of the current cost and performance of trains operating across this corridor including refueling requirements, such as train-fuelling capacity and the timing of train stop according to the service plan, and an account for train refueling via DTL as well as station stop for crew changes and train inspections. Since the project spanned multiple functional groups within BNSF, a joint modeling effort was required to support the team to tackle the simulation project.
With the Implementation Leader’s inside knowledge of BNSF and Visual8’s simulation consulting expertise, a simulation model of the TransCon Traffic flow was jointly developed by the project team.
The model represented the current servicing levels and operating performance of train traffic across the TransCon corridor through the 13 key terminals and train service plans. The terminals with the largest bottlenecks were determined. Fuelling schedules and fuel costs were used to optimize capacity. Inspection rules, crew change requirements, and refueling stops across the various service locations on the TransCon corridor were included to understand the current train service plans. The model was also used to explore the costs and operational issues related to the servicing of trains through the specified terminals and stations across the TransCon.
Visual8 provided BNSF a simulation tool that analyzed and presented various alternatives for expansion of the fueling capacity in 13 key terminals along the TransCon corridor. It also provided fueling schedules that would make optimal use of the terminals. The in-house Implementation Leader took advantage of the accelerated model development program which permitted the user to make internal changes to the model and provided back-up simulation support.