The vision for this key risk area is to continue to reduce the risk relating to freight derailment, with a focus on:

  • asset integrity to ensure that freight vehicles run on suitably maintained infrastructure
  • the identification of emerging risks
  • the operation of rolling stock on the network is as designed, when considering maintenance, inspection, and loading standards.

During 2019/20, 34% of potentially higher risk train accidents involved freight trains (most of these were low-speed derailments). Train axle faults and loading faults were the major precursors to these freight derailments. There was a reduction in these train axle faults and loading faults in 2019/2020 (184 events) compared to 2018/2019 (361 events). The Cross-Industry Freight Derailment Working Group (XIFDWG) had, in 2016, completed a project which involved a bowtie analysis to identify control measures to reduce the number and impact of freight derailments. Some of those controls were put in place and, data from later Wheel Impact Load Detection (WILD) reports for container, bulk, and infrastructure traffic, indicate that the number of vehicles with offset loads is on a downward trend. The introduction of these control measures may also be contributing to the reduction in the derailment data included within the Annual Health and Safety Report.

What the rail industry is doing

In the years since 2017, there has been improved collaborative working between the infrastructure manager, freight operating companies, and their customers. This engagement and collaboration is evidenced in the development of the rail freight project charter and integrated freight safety plan. Progress against these documents is regularly reviewed. Other activities completed include (but are not limited to):

  • Development of freight derailment bowtie and quantified risk analyses.
  • Use of Wheel Impact Load Detection (WILD) reports on offset load between Network Rail, freight operating companies, and major bulk loading customers to reduce the risk of derailment.
  • Publication of a code of practice on bulk loading by the Cross-Industry Freight Derailment Prevention Group (XIFDPG).

Strategic challenges—what industry wants to do

The freight sector wants to work with its customers to develop approaches to ensure vehicles and wagons are loaded in compliance with loading standards. A significant customer in the process of reducing loading risk is Network Rail, and specifically its Supply Chain Operations (SCO) team.

The freight sector also wants to:

  1. Link WILD activations with specific vehicles and wagons, to reduce offset load risks relative to derailment. This will lead to a single source of data that reliably identifies unevenly loaded wagons.
  2. Develop more effective approaches to monitoring dynamic track twist.
  3. Quantify risk and identify emerging trends of vehicles entering the network in an unsafe condition.  Develop a risk management plan that identifies immediate risk reduction initiatives and long-term mitigation objectives.
  4. Monitor the profile of freight risk and prioritise collaborative activities to address key and emerging risks.

How to get involved

There are many opportunities for you to contribute to leading health and safety on Britain’s railways. 

  • Our website hosts a topic hub to help duty holders and XIFDPG members enhance their understanding of, and engagement with, how to reduce freight derailment risk.
  • Freight industry groups are in place to work together to identify and disseminate good practice for freight. All parties across industry are encouraged to engage with these groups: 
  • National Freight Safety Group: the collaborative group overseeing rail freight safety
  • Freight Technical Committee: the engineering focused group
  • Rail Freight Operations Group
  • Cross-Industry Freight Derailment Prevention Group: reports to NFSG, and focuses on reducing the risks of freight derailment due to combinations of dynamic track faults, wagon faults, and offset loads.

Training

RSSB offers Human Factors Awareness Training to help operators better understand why people make mistakes, exploring factors that can influence human performance such as fatigue, workload, and processes and procedures.