Precision Scheduled Railroading and Your Operating Plan (Part 2)

Biarri Rail Colour LogoMarch 8, 2019 – In our last post, I stated that you can’t effectively operate a Precision Scheduled Railroad without an integrated operating plan. All major railroads have an operating plan, but I contend that you need to re-think your planning process if you are embracing PSR.

For most railroads, starting a PSR implementation means building a clean-slate, or zero-based, plan that must start with the analysis of customer demand. Remember that a core tenet of PSR is car velocity, and a plan that is focused on moving the cars (and reducing dwell) will necessarily be built on the demand, or traffic.

I can’t explain the complex steps of an integrated development of a new operating plan in a brief article. Experts spend decades refining their understanding of building operating plans. But, it’s worthwhile to review a summary of the key components:

  1. Customer demand – Demand is at the core of precision scheduled railroading, since block and train design must be based on the projected traffic movement across the rail network. Railroads need to process and analyze their traffic records and waybill files to prepare an historical or projected set of data that can be used for developing blocks and trains. This is frequently the most difficult stage. You can’t run a scheduled railroad without knowing your demand.
  2. Blocking – Most large freight railroads have computer-based blocking tables or algorithms, to help them allocate the projected freight to appropriate blocks. However, many of these same railroads are deficient on tools to help them optimize the creation of blocks that will reduce handling and ton-miles, and improve car velocity. Block design is critical.
  3. Trains – Train schedules should never be developed until the traffic and blocking are well understood and modeled. As with blocks, most of the large NA freight railroads have many software-based tools for designing trains, but there are few deployed solutions for optimizing the block to train assignments. Once again, the key metrics are reduced handlings and ton-miles, using train constraints such as train capacity, power, crewing, and yard and network capacity.
  4. Shared Data – The operating plan uses a set of shared data, of which the most important is the rail network. The network not only includes the characteristics of the route (lat/long, distances, speeds), but it can also contain key variables such as traffic restrictions, physical track characteristics (grade, curvature, etc.), yard capacities, and locomotive HP requirements (load tables).

It is important that all aspects of the operating plan are developed as an integrated whole. A freight rail operating plan is a network problem and you can’t solve for a portion of the network, or for a class of traffic, without impacting the balance of the operating plan. The best way to accomplish this is to develop your plan with an integrated set of automated planning and optimization tools. With these types of tools, it’s also essential to have robust data integration to and from the railroad operational systems.

Asset planning and optimization are also needed to fine tune the operating plan. Locomotive optimization can be used to determine how a fleet of locomotives will be deployed to power trains in a train schedule, balance locomotives, and meet other locomotive demands, such as light engine moves and yard switching. Optimization techniques should also be applied to the other assets such as train paths, car fleets and crew schedules.

Lastly, it is important that the railroad has tools to make incremental changes to the new plan and to develop relative costing for plan scenarios. Quick analysis of planning scenarios can be evaluated using factors such as trip plans, ton miles and handlings, but the ability to examine multiple cost factors (crew, fuel, yard, etc.) with each plan iteration is invaluable.

RailTrends 2018 Conference in New York City

New York City, United States – January, 2019 – Biarri Rail was thrilled to be a first-time sponsor for the annual RailTrends Conference at the Marriott Marquis on November 29-30 in New York City. RailTrends is considered by many to be the premier industry event, where...

Dynamic Scheduling with Local vs Holistic Planning

Many businesses operate in uncertain environments, at the mercy of breakdowns, human error, traffic or the weather. The traditional approach is to build slack into a schedule, to survive some expected level of uncertainty, and then to hope this schedule can be executed in spite of whatever unforeseen events actually occur. In instances where the schedule cannot be implemented as expected, operational decisions are made to try to meet the business goals as much as possible. Under complexity and time pressure, decision makers must often resort to making short term, locally focused decisions without the time or tools to consider implications downstream.

In this blog post, optimisation consultant Dave Scerri describes how recent algorithmic advances and smart tools have enabled the best of both worlds: an operational scheduling approach that responds to changing circumstances while focusing on system wide efficiency.