The Customer Challenge: Long Lead Times for Casted Parts and Complexity Across Aging Fleets Limit Spare Parts Availability

The customer, a Railway Supplier, where procurement is responsible for spare parts availability and sourcing decisions has thousands of different spare parts, many for products over 20 years old. Demand is often low per part but high in criticality for fleet operators. Small batch casting spare parts can take 16–54 weeks to arrive. For older fleets, many parts are rarely in stock, and suppliers or tooling may no longer exist. When parts are reordered, delivery times can extend further.

The result is predictable: Emergency orders, higher inventory, and the risk to slow service delivery to railway operators.

Alternative manufacturing technologies like SLM or DED promise to produce small batches quickly in 2-4 weeks for the client. Rapid Casting is an attractive alternative, using 3D-printed sand molds followed by conventional casting, shortens lead times without changing material or requiring requalification.

But for the railway customer, procurement faced key sourcing questions: Which manufacturing route and supplier can deliver fastest and most cost-efficiently? Should machines be purchased to produce in-house or should parts be sourced externally? Which are qualified materials and suppliers?

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To tackle this, an initiative with 3D Spark was led by the Head of Procurement, with the objective of improving spare parts availability, reducing lead times, and enabling data-driven sourcing decisions across legacy components.

Without data, decisions are guesswork, and sourcing stays limited.

“3D Spark suggests alternative sourcing and manufacturing options for critical spare parts so they can be produced in weeks instead of months, allowing procurement teams to respond faster to customer demands.” Ruben Meuth, CEO & Funder of 3D Spark .

Our Solution: Software Based Part Screening

By analyzing CAD models, ERP data, and technical drawings, the software evaluates technical feasibility, production speed, and cost for each customer part. It quantifies: Lead time reductions, Cost savings and Investment thresholds for in-house machines vs external procurement.

Giving purchasing teams data-driven guidance how to source time critical spare parts.

Results: Faster Delivery and Measurable Impact

• ~33% of parts suitable for Additive Manufacturing (3D printing) with lead times reduced from 16–54 weeks to 1–2 weeks with AM.
• ~25% of parts suitable for Rapid Casting with lead times reduced to 4–8 weeks
• ~10% of parts with direct cost savings with Additive Manufacturing
• Rapid Casting direct part cost savings for ~25% of casted spare parts
• Break-even for in-house Rapid Casting of Molds is at 30–40% utilization.
• Additive Manufacturing machine investment becomes attractive with at least 40 urgent parts/year
• Identified six-digit annual savings potential

This enabled procurement to proactively secure supply for high-criticality parts and reduce dependency on long-lead suppliers.

Takeaways for Alternative Spare Parts Sourcing

Data based part screening by 3D Spark can lay the foundation for:

• Identifying alternative technologies and suppliers to reduce lead time and cost for spare parts quickly
• Proactively securing legacy spare parts, by identifying alternative sourcing routes and technologies for high-risk parts (digital inventory)
• Justify make-or-buy decisions based on ERP, CAD and technical drawing data. 

Want to know how AI-driven part screening can accelerate your spare parts availability and reduce costs? Contact 3D Spark today.