High-Density ASRS for Industrial Spare Parts Distribution
Illustrative scenario based on real deployment patterns. Not sourced from a specific company.
Warehouse Profile
- Warehouse size
- 4,200 sqm, at storage capacity
- SKU count
- 55,000+ with very low average picks per SKU
- Pick frequency
- 30% of SKUs picked fewer than once per month
- Deployment type
- Brownfield
The Situation
High SKU count and low pick frequency mean excessive picker travel time per order. Storage space is exhausted. Many SKUs cannot be delisted despite low velocity — they are critical safety stock with contractual availability requirements. Manual search time per order is growing as the SKU catalogue expands.
Automation Approach
Grid-based ASRS maximises storage density in the existing footprint. Goods-to-person eliminates all picker travel. Low-velocity lines are stored efficiently in the dense grid; fast-movers are positioned for priority retrieval. The system routes retrieval requests to minimise wait time at picking stations.
Expected Outcomes
- 70–80% reduction in picker travel distance per order
- Storage capacity increased 3–4x within the same footprint
- Staff reduced or reallocated to value-adding quality and packing roles
- Same-day dispatch maintained for high-priority orders
Is This Scenario Right for You?
- Deployment
- Brownfield viable with minimum 5m clear ceiling height
- WMS requirement
- Required — order management integration essential
- Budget range
- EUR 1.5M–3.5M
- Payback estimate
- 3–5 years for typical spare parts volumes
Relevant Vendor Types
AutoStore, Exotec, KNAPP.
Browse the Supplier Discussion GuideFrequently Asked Questions
Is ASRS viable for spare parts with very low pick frequencies?
Yes, and the ROI case is often stronger than in high-volume fulfilment. The primary value in spare parts is storage density (reducing the footprint needed for a very large SKU catalogue) rather than throughput. Low pick frequency means robots spend more time retrieving infrequently accessed bins, but the overall throughput required is also lower. The economics work when the storage density benefit is large.
How does a spare parts ASRS handle very large or irregular items?
Most grid-based ASRS systems are optimised for standardised bin sizes. Oversized, heavy, or irregular items (large assemblies, long shafts, etc.) are typically stored in a conventional overflow area adjacent to the automated system. The WMS manages both zones, routing picks to the appropriate location. The ASRS typically handles 60–80% of the SKU range by volume.
Readiness Considerations
- SKU catalogue must be digitised with bin-level location management before ASRS implementation.
- Confirm minimum 5m clear ceiling height with a physical survey, not only building drawings.
- Identify the share of oversized or non-standard items that will not fit standard bins. These require a conventional overflow area.
Supplier Questions to Ask
- QWhat is your standard bin size range and how do you handle SKUs outside those dimensions?
- QHow does the system prioritise retrieval for same-day dispatch requirements?
- QWhat is the expansion path if SKU count or order volume grows by 30 percent within 5 years?
- QHow are slow-moving and safety-critical SKUs stored differently from fast-moving lines?
Assumptions to Validate
- Current average travel distance per pick and how much of picker time is travel versus productive work.
- Storage capacity currently available versus required. How much space relief does the ASRS actually create?
- SKU eligibility for standard bins. A physical sample check prevents surprises during system design.
- Same-day dispatch commitment and whether the ASRS throughput profile supports the required response time.
When This May Not Be the Right Time
- SKU catalogue is not yet digitised or location management is not in place. Catalogue cleanup is the first step.
- More than 30 percent of SKUs are irregular, oversized, or require special handling. ASRS benefit is reduced.
- Ceiling height is under 5m without a confirmed system alternative. Check with suppliers before assuming viability.
Related Scenarios
Does this scenario match your situation?
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