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There is no universally best warehouse automation system. Choose the architecture that fits your order profile, SKU dimensions and weights, peak demand, storage constraint, building, labor model, growth plan, and lifecycle budget. In many facilities, the right answer is a combination: a goods-to-person (GTP) storage system or shuttle subsystem connected by conveyors to receiving, replenishment, packing, sortation, and shipping.
Use the process below to compare options on the same definitions. Do not rank a vendor’s lines-per-hour-per-picker claim against a totes-per-hour-per-aisle claim as if they were equivalent tests.
What each system actually does
The labels describe different parts of a material-flow architecture. Treat them as design categories, not mutually exclusive products.
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Goods-to-person robotics
In a GTP system, automation brings a tote, bin, shelf, or other inventory location to a stationary operator. The picker remains at a workstation while robots or storage equipment present the requested goods. Dematic’s comparison distinguishes several GTP architectures:
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- AMR bin-to-picker: autonomous mobile robots carry bins to a picking station. This approach is positioned around flexibility and scalability.
- AMR shelf-to-person: mobile robots move an entire shelf or rack to the operator. It can suit operations whose inventory is organized in movable shelving rather than standard bins.
- Grid-based storage: an example is AutoStore, in which robots travel on top of a grid, retrieve stacked bins, and deliver them to workstations for picking or replenishment.
- Shuttle-based GTP: systems such as Dematic Multishuttle use automated vehicles within storage aisles to retrieve totes or cartons and feed workstations or downstream processes.
GTP removes walking from the normal pick cycle, but the result still depends on station design, replenishment, induction, software sequencing, exception handling, and the mix of fast- and slow-moving items.
Shuttle systems
A shuttle system uses multiple shuttles that travel in storage aisles. They store, retrieve, buffer, and sequence totes or cartons, then hand them to workstations or another transport layer. Dematic describes Multishuttle in those terms. Swisslog’s CycloneCarrier is another named tote/case shuttle system; its white paper reports up to 2,000 totes per hour per aisle for a specified configuration.
Shuttles are often selected when retrieval capacity, buffering, sequencing, or building height matters more than the maximum flexibility of a free-roaming robot fleet. The shuttle is not necessarily the complete solution: conveyors, lifts, stations, controls, and warehouse-execution software normally surround it.
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A conveyor moves goods or containers between defined process points. It can connect receiving, storage, replenishment, picking, packing, sortation, and shipping. Conveyor sections may include accumulation, merges, diverts, lifts, scanners, and controls, but the exact equipment must be designed around the container and flow.
Calling a conveyor an alternative to every GTP storage technology creates a false binary. Swisslog describes conveyors integrated with shuttle systems and with other automated material-flow equipment. A facility may use a dense grid or shuttle for storage, conveyors for predictable transfers, and mobile robots for areas where fixed routing is impractical.
AS/RS as the wider family
Automated storage and retrieval system (AS/RS) is the umbrella term for equipment that automatically stores and retrieves inventory. Grid systems, shuttle systems, and mini-load crane systems can all fall within that family. The practical decision is which subsystem, or combination of subsystems, handles each activity.
Start with the operation, not the machine
Collect a common data set before asking suppliers for a design. At minimum, include:
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- Average, peak, and seasonal order lines, units, and orders.
- Order shape: lines per order, units per line, single-line orders, and batch characteristics.
- Active SKUs, units on hand, replenishment frequency, and velocity distribution.
- Product dimensions, weights, packaging, fragility, presentation requirements, and whether items can share a tote or carton.
- Required service windows, cut-off times, and the duration and concentration of peaks.
- Available floor area, clear height, columns, docks, fire systems, egress, access routes, and adjacent process areas.
- Current labor by process, ergonomic pain points, training requirements, and tolerance for manual exceptions.
- Expected growth, new channels, SKU proliferation, and the timing of any building expansion.
Dematic’s storage overview says subsystem fit depends on the activity profile and operational considerations. Its positioning—very high density for AutoStore, high-throughput storage and retrieval for Multishuttle, and many storage locations or heavier loads for mini-load AS/RS—is a useful hypothesis to test against this data, not a guaranteed outcome.
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Compare the architectures against the constraints
| Architecture | Where it tends to fit | Questions that can disqualify it |
|---|---|---|
| AMR bin-to-picker | Operations prioritizing layout and process flexibility, with robots carrying bins to stations. | Can the fleet, traffic plan, charging strategy, and station capacity meet the concentrated peak? How will replenishment and exceptions be handled? |
| AMR shelf-to-person | Facilities that can organize inventory on movable shelves and value flexible deployment. | Are shelf dimensions, item presentation, aisle access, and station ergonomics compatible with the SKU mix? |
| Grid-based AS/RS such as AutoStore | Compact, dense storage of suitable small items, with throughput increased by adding robots and stations and capacity expanded by enlarging the grid. | Do item dimensions, access requirements, fire rules, building geometry, and expansion phasing permit the proposed grid? |
| Shuttle storage such as Multishuttle | High retrieval, buffering, sequencing, and use of building height for totes or cartons. | Can the facility absorb a more engineered installation, longer implementation, specialized service access, and the required container standards? |
| Mini-load crane AS/RS | Many storage locations and a broad range of small-load dimensions or weights where crane-based access is appropriate. | Will crane cycle capacity, aisle configuration, container compatibility, and maintenance access meet the peak profile? |
| Conveyor network | Predictable movement between fixed process points and as a connector around GTP or shuttle storage. | Are routes, crossings, merges, accumulation capacity, access, and future layout changes manageable without creating a rigid bottleneck? |
The table describes likely design emphases, not universal performance. A detailed simulation and site survey are required before selecting equipment.
Throughput: keep every denominator attached
Published figures describe different work and system boundaries. Dematic’s comparison reports more than 600 order lines per hour per station for Multishuttle and up to 400 order lines per hour per picker for AMR bin-to-picker. Swisslog’s white paper reports up to 2,000 totes per hour per aisle for its CycloneCarrier configuration. A station, a picker, an aisle, a tote, a pick, and an order line are not interchangeable units.
| Published figure | What it measures | How to use it |
|---|---|---|
| More than 600 order lines/hour/station | Dematic’s Multishuttle comparison claim. | Use as a supplier-stated reference for a named comparison, then request the station layout, SKU assumptions, replenishment conditions, and peak definition. |
| Up to 400 order lines/hour/picker | Dematic’s AMR bin-to-picker comparison claim. | Do not compare directly with station or aisle figures; establish the same order-line definition and labor boundary for every option. |
| Up to 2,000 totes/hour/aisle | Swisslog’s CycloneCarrier white-paper claim for a named configuration. | It is a tote-flow capacity, not a pick-line rate. Ask how induction, retrieval mix, lifts, stations, and downstream transport affect usable output. |
| Up to 20 metres of storage height | Dematic’s described Multishuttle configuration. | Verify building, fire, structural, lift, maintenance, and permitting requirements for the actual site. |
| Up to 24 bins high | Dematic’s described AutoStore grid. | Confirm current design specifications, bin mix, robot access, fire engineering, and usable capacity rather than treating the height as an automatic capacity result. |
These are supplier-published claims, not independent head-to-head benchmarks. No neutral study in the available material establishes a common throughput ranking, uptime result, payback period, or total-cost advantage.
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Average demand can hide the design problem. A system that meets a steady daytime rate may fail when a promotion concentrates orders into a short window. Model at least the average day, the busiest normal day, the seasonal peak, and the required recovery period after a surge.
Order shape matters
Two warehouses with the same number of order lines can need different equipment. Single-line orders may favor rapid presentation and short travel. Multi-line orders may benefit from sequencing and consolidation. A high proportion of repeated units can make replenishment and tote presentation more important than raw robot count.
Separate storage capacity from retrieval capacity
Ask whether the proposed design can add throughput independently of storage. Dematic says an AutoStore installation can increase throughput by adding robots and stations while increasing storage by expanding the grid. Confirm the physical, software, power, and operational consequences of each expansion step; the statement is a supplier description, not a promise that every site can expand without disruption.
Decision factor 2: density, height, and the building
Identify the binding constraint: floor area, clear height, total unit capacity, or access to process areas. A dense grid can release floor space, while a tall shuttle or crane installation can exploit height. Neither creates capacity if fire separation, structural loading, columns, egress, or service access prevents the design.
Constrained footprints
Dematic describes AutoStore as modular for constrained spaces, but notes that fire regulations can create challenges in some situations. Treat local code review as a design gate. Qualified fire-protection, structural, and building professionals must confirm the jurisdiction’s requirements; vendor literature is not local code guidance.
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Usable density is not geometric density
Calculate usable locations after accounting for slow-moving reserve, blocked or inaccessible locations, required empty bins, replenishment areas, work-in-process buffers, aisles, lifts, conveyors, stations, maintenance clearances, and fire provisions. Compare the same inventory service level across concepts.
Decision factor 3: product suitability
Map every SKU family to a handling class. Record length, width, height, weight, center of gravity, packaging stiffness, fragility, contamination risk, and whether an item can be safely picked from a shared tote. Include irregular, oversized, very light, and very heavy products instead of designing only for the median SKU.
Dematic identifies product suitability as a differentiator, but the available comparisons do not establish universal SKU limits across suppliers. Require a written compatibility matrix and physical testing for edge cases. A system that handles most items efficiently may still need a manual zone, special containers, or a second automation subsystem.
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GTP can reduce walking and present work at a fixed height, but labor outcomes depend on station layout, replenishment, scanning, tote handling, rotation, and exception work. Ask operators to test representative tasks, including awkward packaging, short picks, damaged goods, substitutions, and mixed-SKU totes.
Measure the whole labor path
- Receiving induction and container labeling.
- Replenishment from reserve to automated storage.
- Picking, verification, and exception resolution.
- Container closing, consolidation, packing, and sortation.
- Recovery after a robot, shuttle, scanner, or conveyor fault.
- Cycle counting, empty-container handling, cleaning, and replenishment of consumables.
A quoted picker rate that excludes these activities is not a labor plan. Request staffing by process and by shift, with assumptions for breaks, training, absenteeism, maintenance support, and peak overtime.
Decision factor 5: flexibility and growth
Flexibility has several meanings. It can mean moving equipment to a new layout, adding robots, adding stations, changing storage modules, accommodating new container sizes, or rerouting material flow. Ask which type of change the design supports and what work must stop while it happens.
AMR approaches are generally positioned around layout and process flexibility. Grid systems are described as scalable through additional robots, stations, and grid capacity. Shuttle and conveyor systems can be highly productive but are more dependent on engineered paths, lifts, controls, and interfaces. Compare the cost and time of each growth action, not just the initial installation.
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Decision factor 6: implementation and operational disruption
Implementation includes concept design, data validation, detailed engineering, permits, building work, equipment fabrication, software integration, installation, testing, training, cutover, and ramp-up. Dematic qualitatively describes Multishuttle as taking longer to implement than other GTP options; no universal schedule benchmark is established.
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Build a phased cutover plan
- Freeze the baseline data set and agree on the definitions of order line, unit, tote, pick, station, and peak.
- Survey the building, utilities, fire systems, floor loading, columns, access routes, and maintenance clearances.
- Design interfaces for receiving, replenishment, storage, picking, packing, sortation, shipping, and manual fallback.
- Test controls and warehouse-execution software with emulated orders and fault conditions before live cutover.
- Install a pilot or isolated zone where practical, while preserving a manual operating path.
- Train operators, maintenance staff, supervisors, and IT support on normal work and recovery procedures.
- Ramp volume in stages, measuring actual cycle times, exceptions, backlog, and service-level performance against the agreed baseline.
Schedule risk is not limited to equipment delivery. A late fire approval, unavailable shutdown window, incomplete SKU master, or untested interface can delay the whole system.
Decision factor 7: integration and material flow
Draw the physical and information flow before choosing equipment. For each handoff, specify container identity, scan point, destination decision, accumulation behavior, exception route, and ownership of the inventory record.
Systems that must agree
- Warehouse management or inventory software provides orders, locations, inventory status, and replenishment demand.
- Warehouse-execution software sequences work, manages storage strategies and location rules, and coordinates equipment. Dematic identifies its Dematic iQ WES as serving these functions.
- Controls and machine interfaces operate robots, shuttles, conveyors, lifts, scanners, and safety devices.
- Labor and packing applications confirm picks, exceptions, and shipment completion.
Swisslog’s examples of shuttles integrated with AGVs and pallet and light-goods conveyors illustrate why system boundaries matter. A storage device can meet its internal cycle target while the overall operation misses service levels because induction, packing, sortation, or shipping is undersized.
Decision factor 8: lifecycle economics
Compare total lifecycle cost rather than the equipment purchase price. Build the same scenario model for every concept and state every assumption.
Include these cost categories
- Equipment, installation, controls, software licenses, integration, engineering, and commissioning.
- Building modifications, structural work, utilities, fire protection, permits, and temporary operating space.
- Labor changes in picking, replenishment, packing, supervision, maintenance, IT, and safety.
- Energy, consumables, spare parts, preventive maintenance, service contracts, and training.
- Downtime exposure, manual fallback capacity, planned shutdowns, and recovery from faults.
- Expansion modules, additional robots or stations, new containers, software changes, and future building work.
- Decommissioning, relocation, or residual-value assumptions if the facility strategy may change.
The available vendor pages do not provide an independent apples-to-apples total-cost or payback model. Ask each supplier to price identical demand scenarios, service levels, operating hours, peak definitions, labor assumptions, and system boundaries. Keep one-time installation costs separate from recurring costs and show sensitivity to volume, wages, energy, and peak concentration.
A practical selection procedure
- Define the service promise. Set order cut-off times, dispatch windows, accuracy targets, peak recovery expectations, and acceptable backlog.
- Clean the data. Reconcile SKU dimensions and weights, inventory history, order lines, seasonality, replenishment events, and exception records.
- Segment the inventory. Separate fast, medium, slow, bulky, fragile, irregular, and special-handling items. Identify which segment creates the bottleneck.
- Map the current flow. Document receiving through shipping, including manual touches, scans, buffers, queues, and failure routes.
- Set physical gates. Eliminate concepts that cannot meet height, floor loading, fire, egress, access, utility, or maintenance requirements.
- Define comparable scenarios. Give every bidder the same average, peak, seasonal, growth, SKU, and operating-hour cases.
- Normalize performance claims. Convert outputs to agreed units such as completed order lines per hour at the shipping boundary, while preserving the supplier’s original denominator beside the normalized result.
- Model labor and exceptions. Include replenishment, packing, cycle counting, downtime recovery, training, breaks, and manual fallback.
- Test integration. Require emulated orders, inventory discrepancies, blocked locations, lost containers, equipment faults, and restart procedures.
- Score lifecycle value. Compare five- and longer-horizon costs, expansion steps, risk allowances, and operational disruption under the same assumptions.
- Validate with operators. Run ergonomic trials and review maintenance access, cleaning, noise, visibility, and emergency procedures.
- Choose a staged roadmap. Specify what is automated first, what remains manual, how capacity is added, and which metrics trigger the next investment.
When each approach is a plausible starting point
Choose GTP robotics as the lead hypothesis when
- Reducing picker travel is a major objective.
- Layout or process flexibility is more valuable than maximum fixed-path density.
- Inventory can be presented in compatible bins, shelves, or totes.
- Throughput can be increased through additional robots or stations, subject to a site-specific capacity model.
Choose shuttle storage as the lead hypothesis when
- High retrieval, buffering, or sequencing demand is concentrated in tote or carton flows.
- Building height is available and can be engineered for the required storage and service access.
- The operation benefits from a tightly controlled, high-capacity storage core.
- A longer, more engineered implementation can be scheduled without unacceptable disruption.
Choose conveyors as the lead transport layer when
- Process points are stable and volumes justify fixed routes.
- Receiving, storage, picking, packing, sortation, and shipping need predictable transfers.
- The conveyor can be integrated with a GTP or shuttle subsystem rather than forced to perform storage work it was not designed to do.
Use a hybrid architecture when constraints differ by zone
A dense grid can handle small, suitable items; a shuttle can buffer or sequence totes; conveyors can connect fixed processes; and AMRs can serve irregular or changing areas. The hybrid must still have one coherent inventory model, controls strategy, safety design, and exception process.
Common evaluation mistakes and how to correct them
Mistake: selecting the highest published rate
Correction: preserve the denominator and configuration, then model the complete path to a shipped order line.
Mistake: treating conveyors and storage automation as substitutes
Correction: assign each technology a process responsibility and design the handoffs between them.
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Mistake: sizing to average demand
Correction: test concentrated peaks, seasonal surges, recovery time, replenishment bursts, and downstream packing capacity.
Mistake: assuming geometric density equals usable capacity
Correction: subtract buffers, empty containers, blocked locations, maintenance access, fire provisions, and required service levels.
Mistake: ignoring the difficult SKUs
Correction: test the largest, heaviest, most fragile, least stable, and least frequently handled items and define a deliberate manual or alternate zone.
Mistake: pricing only the installation
Correction: include software, integration, energy, maintenance, labor, downtime, building work, training, and expansion in one lifecycle model.
Mistake: postponing code and permitting checks
Correction: involve qualified local designers and authorities before freezing height, grid, aisle, fire, and egress decisions.
Questions to put in every supplier proposal
- Which exact configuration, container sizes, SKU limits, and operating assumptions support each quoted rate?
- Is the rate measured at a picker, station, aisle, machine, or shipping boundary?
- What peak duration, recovery period, uptime assumption, and exception rate are included?
- How are replenishment, induction, packing, sortation, and shipping capacity sized?
- Which modules, robots, stations, grid sections, shuttles, lifts, or conveyor zones can be added later?
- What building, structural, fire, access, and maintenance requirements must be approved?
- What happens during a robot, shuttle, conveyor, scanner, network, or software failure?
- Which tasks remain manual, how many people perform them by shift, and how are breaks and training modeled?
- What data, interfaces, test scripts, cybersecurity controls, and support response times are included?
- Which costs are one-time, recurring, volume-dependent, or triggered by expansion?
- What customer references or acceptance tests demonstrate the same product profile and peak behavior?
What the evidence can—and cannot—tell you
Dematic’s comparative analysis says GTP solutions such as Multishuttle, AutoStore, AMR Bin-to-Picker, and AMR Shelf-to-Picker use similar principles but differ in storage and pick-station technologies, operator pick rates, ergonomics, suitable products, density, throughput flexibility, security, scalability, and maintenance. That is a useful checklist of decision dimensions, not proof that one architecture wins every site.
Swisslog’s white paper says, “AutoStore is an extremely powerful automation solution in the right application but may not be ideal for every situation.” Its alternatives include autonomous goods-to-person robots where density is less important, mini-load cranes for varied small-load dimensions and weights, and shuttle systems for tote and case storage. Those descriptions help generate options; they do not replace a common data set, site survey, simulation, or lifecycle model.
The defensible conclusion is therefore conditional: select the system that satisfies the operation’s service promise with acceptable building risk, labor exposure, maintenance burden, expansion path, and lifecycle cost. Vendor claims can narrow the field, but only comparable assumptions and site-specific validation can select the final design.
Quick Recap
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