Retrofit makes existing rail vehicles and components fit for the future. Targeted modernization instead of new purchases saves costs, extends service life, and increases sustainability—a strategic advantage for operators. Read the blog post now to learn more!
3D printing is revolutionising the supply of spare parts in the railway industry – fast, flexible and sustainable. But does this spell the end of the used parts market? This article shows why additive manufacturing and used parts will work hand in hand in the future – as two sides of an efficient, digital spare parts strategy.
Predictive maintenance uses sensors, AI and data analysis to predict machine failures before they occur. This enables companies to reduce maintenance costs, avoid downtime and extend the service life of their equipment.
Companies in the railway industry are regularly faced with the question of whether to recycle or scrap disused vehicles and components. While scrapping means final disposal, recycling through reuse, recycling and the sale of used parts opens up economic opportunities and conserves resources. Recycling takes precedence in law because it reduces costs, saves CO₂ and strengthens the recycling cycle. Only when reuse is not technically or economically feasible does scrapping remain the last option.
A well-thought-out inventory strategy in maintenance prevents downtime and reduces costs. Models such as just-in-time, safety buffers or principles such as FIFO, LIFO and on-demand each have advantages and disadvantages. While JIT saves costs, buffer stocks increase availability but tie up capital. With clear priorities, risk analyses and digital tools, the right balance can be found – for maximum operational reliability and efficient warehousing.
Efficiency, transparency and new opportunities. The rail industry is facing a digital revolution: online platforms such as railauction.plus simplify procurement processes, save time and create market transparency. At the same time, they enable more flexible, sustainable and Europe-wide networked business models – a real added value for operators, workshops and suppliers.
AI technologies are becoming increasingly important in modern spare parts searches in the railway sector. Aging fleets, with their unique variety of parts, present a complex puzzle for maintenance teams. As trains age, documentation becomes fragmented and many critical parts become obsolete. The solution? AI spare parts search and data optimisation.