Unmanned Dark Store: Planning WMS and Automation correctly

The term dark store is used in logistics to describe two different warehouse concepts. It can refer to a highly automated, largely lights-out warehouse. It can also refer to an e-commerce warehouse designed like a supermarket that uses the principle of a “shopfloor layout for many single-item picks.” However, instead of customers, pickers move through this store. 

Parts 1 and 2 of our miniseries focus on the lights-out dark store and explain how warehouse management systems and warehouse automation work together to ensure stable and cost-effective operations, especially for mid-sized companies. Part 3 of the miniseries then addresses the specific requirements and solution approaches for the dark store as an e-commerce picking warehouse:

• Article 1 examines the target vision and specific requirements for WMS and automation in a lights-out dark store
• Article 2 describes SME-oriented solution strategies and implementation, including scaling of the lights-out dark store
• Article 3 describes processes, KPIs, partial automation, and WMS optimization for the dark store used for e-commerce picking
  
  

Dark Store: Target Vision for mid-sized Companies 

When we refer to “lights-out” operations in warehousing, this describes a gradual state. In standard operations, putaway, replenishment, and order processing run without continuous manual intervention, while goods receipt and fault resolution remain deliberately planned. Suitable profiles include stable packaging rules, reliable master data, and an order mix that can be translated into standardized processes. 

Requirements for WMS and automation in a lights-out dark store 

1. Real-time Inventory Accuracy 

Inventory must not only be correct but also clearly and digitally traceable at all times. Every material movement must be clearly assigned to a specific object, such as an item, container, or load carrier. If this assignment is missing or ambiguous, the system can no longer be reliably controlled or planned. 

1.1 Implications for the WMS: 

Need for a strict Identity Concept 

Every physical unit in the warehouse requires a unique identifier so that movements can always be clearly assigned. The following identifiers are typically used: 

• Serial number or internal tracking ID: This refers to a unique number for a logistical unit, such as a carton, container, or pallet, regardless of which items are inside.
• SSCC (Shipping Container Code): This is a globally unique number from the GS1 standard, frequently used for pallets or shipping units.
• Container IDs are unique identification numbers for reusable load carriers such as crates, trays, or tote boxes. They are especially important when systems like shuttles or conveyor technology operate with containers.

Rules for Quarantine, Clarification Cases, and blocked Stock 

The WMS must define rules for the following exception cases: 

• Quarantine means that goods are temporarily blocked because something needs to be checked—for example, damaged goods, unclear quantities, missing labeling, or quality inspections.
• Clarification cases are processes where the target state and the actual state do not match. Examples include discrepancies after counting, a missing container, a scan error, or an unconfirmed movement. The system requires defined workflows so that such cases do not get lost in day-to-day operations.
• Blocked stock refers to inventory that may not be used for technical or legal reasons, such as expiry date issues, quality deviations, recalls, hazardous material clearance, or reservation for a complaint.

Cycle Counting and Plausibility Checks as standard Processes 

• Cycle counting means continuous inventory counting. Instead of counting everything once a year, selected storage locations or items are counted daily or weekly. This allows discrepancies to be detected early and inventory to remain reliable.
• Plausibility checks are automated validation rules in the system that detect inconsistencies before they lead to disruptions. Examples include negative inventory, movements without a source or destination, quantities outside expected tolerances, or a container that, according to the system, would have to be in two locations at the same time.

1.2 Implications for Automation 

Scans, Sensors, and Weight Checks at the right Points 

Automated systems must verify what actually happened at handover points—for example, during induction and discharge, at transfers between conveyor technology and shuttles, as well as at packing and shipping stations. Scans capture barcode or RFID identifiers, sensors detect presence and direction, and weight checks verify whether contents and quantities are plausible. 

Defined Diverters and Buffers for Exception Cases 

Unreadable labels, mis-scans, or implausible weights do occur. To prevent the main flow from stopping, diverters to a clarification area and buffer lanes for temporary parking are required. Clear rules are essential for how these units are checked and reintegrated into the process. 

2. Orchestration instead of List Logic 

The system requires continuous, prioritized decisions about what should happen next. Simple pick lists are insufficient, as multiple resources must be served in parallel. 

2.1 Implications for the WMS 

• Orders are released in a way that ensures service levels, cut-off times, and shipping rules are met.
• The sequence of orders is controlled to match packing stations and the consolidation of multiple partial orders, and adjusted as needed.
• The system manages capacities and states of containers, trays, buffer lanes, and workstations.

2.2 Implications for Automation 

• A warehouse execution system or warehouse control system continuously controls transport orders and material flow based on the current situation. Capacity limits, buffer fill levels, and avoidance of congestion within the system are taken into account.
  
  

3. Robustness to Disruptions and Recovery 

Lights-out operation only works if exceptions do not lead to a standstill. Disruptions must be handled reproducibly, with clear states and safe restart procedures. 

3.1 Implications for the WMS 

• Clear procedures are defined for exception cases, with every status change unambiguously specified.
• Roles and access rights are clearly regulated, control room functions enable targeted interventions, and all actions are transparently logged.
• Protective mechanisms are implemented to ensure that confirmations are neither processed twice nor lost.

3.2 Implications for Automation 

• Regular availability messages, clear fault codes, retry strategies, and clearly defined restart steps are implemented.
• In addition, buffer areas and manual intervention points are provided so that material flow is not blocked in the event of disruptions.
  
  

4. Replenishment as a Core Process 

Performance points must not run dry. In automated dark stores, replenishment is the most important stability function. At the same time, the system must not become overloaded: too much or overly rapid replenishment can overload buffers, conveyor lines, transfer points, or workstations, leading to congestion and priority conflicts with actual order processing. Replenishment therefore requires controlled pacing and clear capacity limits. The goal is a controlled throughput in which replenishment reliably supplies picking without clogging the overall system at bottlenecks. 

4.1 Implications for the WMS 

• Replenishment is triggered either via forecasts or via fixed rules.
• Separate logic is used for fast- and slow-moving items, and minimum stock levels are safeguarded at relevant performance points.
• Replenishment is synchronized with order intake and cut-off times.

4.2 Implications for Automation 

• A balanced mix of priorities between putaway, replenishment, and picking is defined.
• Empty runs and unnecessary relocations are systematically avoided.
  
  

5. Data and Interfaces as operational Risks 

All involved systems must use the same information and know the same status at all times—namely the ERP (enterprise resource planning system), the order management system, the online shop, the shipping service providers’ systems, the automation system, and the WMS. If messages arrive late or different states are stored, inventory errors occur and the process can stall. 

5.1 Implications for the WMS 

• Order, reservation, inventory, and shipping status are clearly separated from one another and unambiguously defined.
• A clean event and messaging model ensures that duplicate messages do no harm and that changes are traceably versioned.
• Interfaces and data quality are monitored through continuous monitoring.

5.2 Implications for Automation 

• A clear, reproducible confirmation is generated and processed for every movement.
• Inventory and technical status are reconciled at clearly defined synchronization points.