CSX Solves Railroad Operation Challenges with and without AnyLogic Rail Library

CSX is a railroad company that operates about 21,000 route miles (34,000 km), including one of the three Class I railroads, which serves most of the East Coast of the United States, and reaches nearly two-thirds of the country’s population.


The Network Planning division’s role is critical to the company’s success. This division identifies where to add capacity to accommodate future growth, ensures infrastructure can support and sustain a high level of service, and tries to improve the efficiency of capital spending.


Network Planning uses a multistep approach to manage the network capability. They utilize analytical tools to monitor current service levels, identify appearing problems, and determine the root cause of these disruptions (if the problem is operational or infrastructural).


In addition, they analyze what possible solutions can be applied to the problem, including investment decisions, and which of these decisions will provide the best financial return. To get the right answers, the use of traditional analytical tools is insufficient. That is why, for these purposes, CSX employs simulation modeling technologies. They use AnyLogic software for many different purposes because it allows them to create models of various systems, at the required abstraction level, with a quick turnaround time.


AnyLogic allows the railroad industry users to simulate line-of-road, terminal, and yard problems. The following three projects, completed by CSX in 2014, covered a variety of tasks that were solved using AnyLogic software.


MGA Line Investment Planning

Problem:




A rail line that is jointly owned by CSX and their competitors was expected to see a large growth in demand from several coal mines. The high competition between the two companies meant that if one of them could not fulfill the demand, the other one would do so. CSX needed to identify the best operational/capital strategy to handle the increased business. They wanted to know the answers to these specific questions:

  • Did they have enough staging capacity on the line to stage empty unit coal trains to respond quickly to the new demand?  
  • Where were the best locations on the line to add the additional staging capacity if needed?

They utilized AnyLogic simulation modeling to find the answers.


Solution:

Rail Line Simulation Model

MGA Rail Line Simulation


The created supply-chain network model simulated the demand of empty trains from five coal mines, as well as the fulfillment of the demand, and staging of empty trains. The trains were modeled as agents moving across the network. By varying values of relevant parameters, users could infer the impacts of different factors to the train throughput (i.e. staging capacity, as well as loading speeds at the coal mines).


The model calculated the company’s achieved throughput, and the business lost by CSX, due to the lack of available trains.


Outcome:




The model provided a way for decision makers to gain insight into the system to help identify the maximum possible throughput. The simulation showed that the company did not have enough staging capacity to serve the increased demand, and it helped distinguish the highest priority capital investment projects to implement.

Locomotive Shop Optimization

Locomotive Shop Simulation Model


Nashville Locomotive Shop Redesign

Problem:




The CSX’s Nashville locomotive shop needed to be expanded in order to meet the higher level railroad network redesign. The facility included a quality maintenance shop and a roundhouse. The company’s mechanical department needed to select the best layout design from eight alternatives. The objective was to identify the layout that maximized the throughput of locomotive processing.

Solution:




This project utilized the special AnyLogic Rail Library to build a model of the locomotive shop and test the different designs.


In the model, 72% of the incoming locomotives went to the roundhouse, while 22% went to the maintenance shop. The remaining 6% could go to either of them, depending on the problem they had after further inspection. Service times in both shops differed.

Locomotives moved at five miles per hour in the system. There was one common queue, with nine spots, for both shops. A locomotive was pulled into the system if there was a spot available in the roundhouse, the maintenance shop, or the common queue. The numbers of spots available in both shops and in the queue were parameters that could be varied by the user.

Outcome:




The model was used by the mechanical department to test their assumptions by experimenting with the system, and as a decision support tool to determine which layout configuration was best. The model helped the specialists drive the conversation among the stakeholders and base their solution on the reliable data.


Network Performance Emulator

The company faced greater than expected demand growth, coupled with hard winter weather and resource constraints, which led to congestion on the northern tier of the CSX network. When they analyzed this problematic situation afterwards, the Network Planning team was trying to determine what happened on the network and could avoid these issues in the future.


As the research continued, they found out that it would be easier to understand the processes if they replaced the traditional analytical methods with a visual emulator. So, they decided to reproduce, or replay, the past system behavior in AnyLogic with the use of animation on a GIS map to better understand density, flow, and congestion processes in the network and improve decision making. All of the train movement data was imported to AnyLogic from the databases, predefining the behavior of the trains in the model. The emulator included the animated train movement with statistics and indicators making the data visually understandable.


The model was presented to the C-level officers and the customers and helped drastically raise the understanding of the issue among the stakeholders.


Rail Network Simulation

Rail Network Emulator



Watch the video of Jeremiah Dirnberger from CSX presenting these case studies at the AnyLogic Conference 2014:


More Case Studies

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    Aurizon is an Australia’s largest rail freight operator, managing more than 700 locomotives and more than 16,000 wagons. Aurizon is widely engaged in coal, iron ore, and mineral transportation. In order to increase operational efficiency the company decided to move one of their rail yards to other town. This rail yard was mainly engaged in wagon and locomotive maintenance and locomotive preparation.
  • Selecting the Best Inventory Policy Using Gojii
    Existing supply chain and S&OP tool sets do a great job of managing supply to meet a selected "forecast." However, there is no single "correct forecast" of future demand, and existing tools are not designed to select the best demand level for the business. There is a "tool gap" between forecast inputs and selection of the best demand signal (aka "forecast") to drive your S&OP system. Gojii is the tool created by DecisioTech that fills that gap.
  • Maximizing Push Boat Fleet’s Net Voyage Revenue
    InterBarge, a first-class waterway operator, affiliated with SCF Marine, a part of Seacor Holding Group, operates freight along the HPP Waterway (Hidrovia Parana Paraguay, located in Argentina, Paraguay, Brazil, and Uruguay) on a dedicated contract carriage. The company’s challenge was to use the boat capacity free from dedicated contract commitment as a fleet, maximizing net voyage revenue.
  • Customer-Centric Transportation Network Modelling
    The public transportation company employed PwC Australia to develop a solution that could provide a customer-centric view of their railway infrastructure and help the company understand the current incident effects on rail network operations and how to improve the situation. PwC consultants decided to build a model of the transportation network that would simulate train movements, incidents, and customers at stations and in trains.
  • Preventing “Bus Bunching” with Smart Phone Application Implementation
    In public transport, bus bunching refers to a group of two or more transit vehicles (such as buses or trains), which were scheduled to be evenly spaced running along the same route, instead running in the same location at the same time. Dave Sprogis, Volunteer Software Developer, and Data Analyst in Watertown, MA, used AnyLogic to confirm his thesis that preventing "Bus Bunching" would improve the experience of public transit bus riders.
  • Emergency Evacuation Planning: Minimizing Gridlock and Improving Public Safety
    A typical rush hour impedes the mobility of individual vehicles and significantly slows the overall flow of traffic. This phenomenon is compounded by events of mass mobilization, such as during an evacuation due to a hurricane or other event. When this occurs, traffic can reach a state of gridlock. ITS researchers sought to understand how public safety could be improved during such events by incorporating communication among a percentage of the vehicle population.
  • Supply Chain Design for Vaccine Manufacturer
    GlaxoSmithKline (GSK) was the world’s sixth largest pharmaceutical company in 2014. The company was launching a new vaccine product on a new market that needed a distribution network different from what they had before. Therefore, the company needed to design a new supply chain and align manufacturing processes with it.
  • Apparel Company Chose Location for New Distribution Center Using Simulation Modeling
    Fruit of the Loom (FOTL) is one of the largest US apparel manufacturers and marketers. The company was expanding, and the executives wanted to know if it would be beneficial, in terms of shipping costs, to add a new distribution center (DC) on the east/west coasts of the US, or to redistribute products to a pre-existing DC. The contractors decided to simulate the whole supply chain in order to visualize DC locations on a GIS map, and the supply network between them.
  • Improving Mining Outbound Logistics with Agent-Based Simulation Modeling
    One of the largest resource companies in the world, with over $80 billion in sales, decided to enter a new market. It was planning to build a new potash mine with 90% of the resources exported. They wanted to design a reliable supply chain, with a high speed of supply replenishing, and the ability to recover from natural disasters and man-made crises benefiting from such volatility. Amalgama and Goldratt companies contracted this project to design the potash mining operations and a full supply chain of outbound logistics.
  • Simulation of the Construction of a Tunnel with a Tunnel Boring Machine
    The cost of one hour of down time of a tunnel boring machine is usually high and project managers have to do their best to avoid unnecessary delays in construction. The aim of the simulation project, which was carried out at Ruhr University Bochum in Germany, was to create a simulation model that would be capable of determining the bottlenecks in tunnel building processes in order to minimize the possible monetary losses.