In the world of railway infrastructure, efficient track upgrades are crucial to ensuring smooth operations, safety, and reliability. Achieving efficient track upgrades can be challenging due to several variables, tight schedules, and budget constraints. This is where data-driven workbank planning becomes invaluable.
What Is Workbank Planning?
A workbank is a set of planned works, whether renewals, maintenance or enhancements, usually for a single asset type, domain or discipline. Planning is essential: budgets must be forecasted and requested, resources must be allocated, deliverability assessed. Whether looking at the short-, medium- or long-term, workbank planning is a core activity for all asset management teams. A coherent plan ensures assets are renewed and maintained in a timely fashion in order to meet safety, reliability and performance targets.
Data-driven workbank planning pushes the envelope for traditional methods of planning by making informed decisions using historic data and predictive analytic. By tapping into a data warehouse of information (including previous maintenance records), rail operators can significantly optimise track upgrade projects.
Planning Optimisation
Among the major challenges of track upgrade projects, one of the major factors has been ensuring effective resource utilisation. Workbank planning provides a clear overview of resource availability, offering several possibilities to make better decisions. By analysing performance data from the past, this can helps rail operators assign the right resources at the right time to avoid bottlenecks and delays.
Poor planning, unforeseen delays, or mismanagement of resources can often lead to budget overruns in track upgrade projects. workbank planning helps to develop realistic cost estimates and determine possible avenues to save costs using data analytics. Cost data from previous projects, together with predictive analytics, can show the best way to perform upgrades.
Risk Management
Track upgrades come with a variety of risks, from equipment failure to environmental challenges and safety concerns. With data-driven workbank planning, rail operators can use previous data and predictive analytics to identify risks early and implement proactive solutions. Data collected can detect anomalies and allow for pre-emptive maintenance, reducing emergent works during upgrades. Forecasts of what is likely to go wrong let planners adjust the schedule of the upgrade work and modify their risks. We took a closer look at the different types of maintenance in our article Maintenance Strategies: Preventative, Corrective, And Emergency.
Previous Project Assistance
One of the most important features of workbank planning is to help inform future projects. Rail operators can utilise data from prior upgrades to sharpen and improve their planning processes.
When completing an upgrade plan, rail operators can look at the data collected and use that to implement corrective measures for future upgrades. This becomes an iterative process that, with time, leads to more efficient workbank planning, reduced project timelines, and better outcomes. Data-driven workbank planning is the game-changer for railway track upgrades.
For more information about our platform and to see how using business intelligence can significantly improve your planning for rail maintenance, upgrades and more, contact one of our team today for a demo of our rail planning platform.