When carrying out rolling stock maintenance, companies face various challenges. For instance, if a maintenance facility’s total load increases, it might lead to further disruptions in working processes. To address the issues, including traffic congestions and fleet mix inefficiencies, and at the same time maximize throughput, railway yard redesign may be needed. For this purpose, the current facility layout may be simulated to later analyze its malfunctioning parts, and then test innovations in the model to make the layout more efficient and sustainable.
Advisian, an independent consulting arm of the WorleyParsons Group, with subsidiaries in 19 countries, was tasked with modeling one of Australia’s largest rail maintenance centers. This center is used for the planned maintenance, repair, and stabling of both regional and suburban rolling stock. The depot suffered from considerable congestions and the managing company wanted to find out the reasons and work out the techniques for congestion elimination. The managing company also wanted to test train depot design at its maximum capacity, taking into account infrastructure constraints and optimize fleet mix.
Advisian’s role was to develop a railroad simulation tool which could be used to:
- Determine the overall efficiency and effectiveness of the depot.
- Analyze the effect of new fleets on the facility.
- Identify constraints on operations.
- Test the impact of depot infrastructure changes.
With simulation, Advisian was able to create a digital copy of the maintenance facility and its operations, analyze its dynamics, and test different scenarios of improving the workflows in the depot.
Advisian chose AnyLogic rail yard management software to simulate the depot operations. The company made extensive use of the AnyLogic Rail Library, a toolkit for detailed simulation of railyard operations. It not only provided the ready-to-use objects with predefined logic for maintenance facility simulation, including railcars, locomotives, and rail tracks, but also allowed for creating realistic 2D and 3D animation for the model.
The facility was utilized by different train types, which is why the simulation team mirrored the functioning of fleet mix in the model, identified how the processes inside the facility were changing in real time, and gained insights concerning possible structural changes.
The simulated operations were based on data from actual train timetables. AnyLogic data input capabilities also permit the connection of a model with a database and feeding the model in offline mode, or with real-time data. The detailed model also helped uncover hidden interactions to gain an understanding of the railcar repair yard processes and improve their efficiency.
The major insights, however, were driven by model statistics. It helped capture the behavior of the simulated system and analyze indicators, which were important in the depot’s functioning. For instance, for congestion avoidance and other purposes, it was vital to understand the utilization of railways in certain areas of the depot. This led to gathering utilization statistics per each area and displaying it on graphics for further analysis. The statistics data could then be easily exported in Excel format.
With AnyLogic, the simulation team was able to identify:
- The depot’s maximum capacity, considering infrastructural and process constraints.
- Bottlenecks within the facility’s current layout. They were the cause of significant congestion across the facility.
Simulation allowed for a deeper analysis of depot operations, as well as for implementing, testing, and assessing the effect of potential changes in both the fleet mix and the facility layout.