In the modern rail industry, where downtime can mean significant delays and efficiency is paramount, predictive maintenance has emerged as a solution to address equipment failures and optimise maintenance schedules. This approach utilises data analytics, machine learning algorithms, business intelligence and (where available) sensor technology to predict when parts are likely needing to be replaced […]