The Mixed-Case Palletizing Challenge
Consumer goods manufacturers face a problem that has grown steadily worse over the past two decades: SKU proliferation. Retailers demand more variety, smaller lot sizes, and store-ready pallets built from multiple product types. The traditional approach—dedicated palletizing lines for each product family, with manual labor bridging the gaps—breaks down when you're running 200+ active SKUs across a facility that ships mixed-case pallets to dozens of distribution centers.
That was the situation facing a mid-sized consumer goods manufacturer producing household cleaning products. Their end-of-line operations had become the bottleneck. Manual palletizing stations ran multiple shifts, turnover was high, and repetitive strain injuries were climbing. And the real constraint wasn't labor cost alone—it was the inability to build mixed-case pallets accurately and quickly enough to meet retailer shipping requirements.
The manufacturer needed a system that could handle multiple product sizes and weights within a single palletizing cell, build stable mixed-case pallets according to retailer-specific patterns, and do it at rates that would consolidate multiple manual stations into a single automated solution.
Defining the Technical Requirements
Before any equipment was specified, the engineering team documented the actual operational requirements. This upfront work is where most palletizing projects succeed or fail. The key parameters included:
- SKU dimensions: The full range of case footprints, heights, and weights the cell must handle, from the lightest aerosol cases to the heaviest cases of liquid product
- Throughput target: The sustained rate the cell must hold, plus the burst capability needed for high-demand SKU runs
- Pallet configurations: Every retailer-specific pallet pattern in use, plus a default mixed-case pattern
- Changeover: Zero mechanical changeover between SKUs—pattern changes handled entirely in software
- Layer stability: Interlayer slip sheets on selected patterns, corner boards on all pallets
The weight range was particularly challenging. A gripper system that handles a light case of aerosol cans needs a fundamentally different approach than one moving heavy cases of liquid detergent bottles. The solution required either a universal gripper or a quick-change system that wouldn't eat into cycle time.
System Design and Integration
The final system centered on a high-payload robotic cell with a custom end-of-arm tool designed for the full case range. The EOAT used a combination of vacuum zones and mechanical clamping. Vacuum provided primary grip for lighter cases, while pneumatic clamps engaged automatically for heavier products. A pressure sensor array confirmed grip integrity before any lift, preventing drops that would damage product and create line stoppages.
The cell layout addressed material flow from multiple upstream packaging lines converging into a single palletizing station. An accumulation conveyor system fed cases into a sequencing area where a vision system identified each case by barcode and dimensional profile. The sequencing logic was critical—cases had to arrive at the robot in the correct order to build stable pallet layers without requiring the robot to buffer or resequence product.
The conveyor design incorporated several features specific to mixed-case handling:
- Singulation section that separated cases arriving in groups from higher-speed upstream lines
- Right-angle transfer for routing cases from the inbound lines to the sequencing conveyor
- Dynamic accumulation zone providing enough buffer per line for the robot to absorb brief upstream interruptions without stopping packaging operations
Pallet build patterns were stored in the robot controller and selected automatically based on order data pulled from the warehouse management system. When a new pallet order started, the system knew which SKUs would arrive, in what sequence, and which pattern to execute. The operator's role shifted from physical case handling to monitoring the HMI, loading empty pallets, and removing completed ones—though even pallet loading was semi-automated with a pallet dispenser feeding the build station.
Software and Pattern Management
One of the underappreciated aspects of mixed-case palletizing is the software complexity. Each retailer pattern defines not just where cases go on each layer, but the sequencing rules that determine build order for stability. A heavy case of liquid detergent must go on the bottom layer. Tall, narrow cases need adjacent support. Lighter aerosol cases sit on top.
The system used offline pallet pattern software that allowed the engineering team to design and simulate new patterns without interrupting production. Each pattern was validated against stability criteria—center of gravity, overhang limits, weight distribution per layer—before being released to the production system. When a retailer changed their pallet specifications, the manufacturer could develop, test, and deploy a new pattern offline rather than reprogramming the robot on the line.
This software-driven approach also enabled something manual palletizing never could: perfect consistency. Every pallet built to a given pattern was identical. No variation between shifts, no degradation during overtime hours, no quality issues caused by operator fatigue. Retailer chargebacks for incorrect pallet builds, a recurring cost under manual palletizing, fall away once every pallet is built to a validated pattern.
Results and Operational Impact
Once the cell is running, optimization of conveyor speeds and robot path planning during commissioning is what turns a system that meets its throughput target into one with headroom to burst during high-demand SKU runs.
The operational impact of consolidating manual palletizing into a single robotic cell lands in the same places where manual palletizing was failing:
- Labor: Operators move from physical case handling to a small monitoring role at the cell, with the rest redeployed to upstream packaging roles where manual dexterity is still required
- Throughput: A single cell palletizes more cases per shift than the manual stations it replaces
- Pallet quality: Retailer chargebacks for pallet build errors are eliminated because every pallet is built to a validated pattern
- Injury reduction: Repetitive strain injuries in end-of-line operations go away with the manual lifting
- Floor space: Several manual palletizing stations consolidate into a single cell with a smaller footprint
The ROI calculation for a system like this is straightforward: annual labor savings, chargeback elimination, and injury cost reduction are weighed against the total system cost—robot, EOAT, conveyors, vision, controls, safety guarding, installation, and commissioning.
Lessons Learned
Several insights from this project apply broadly to mixed-case palletizing implementations in consumer goods packaging automation environments:
Invest in upstream sequencing. The robot itself is rarely the constraint. Getting cases to the robot in the right order, at the right rate, without gaps or bunching, is where most of the engineering effort belongs. The manufacturer initially underestimated the complexity of merging multiple packaging lines into one palletizing cell and had to redesign the accumulation conveyor section during commissioning.
Plan for SKU changes from day one. Consumer goods manufacturers add and discontinue SKUs constantly. The system's case handling envelope—the range of dimensions and weights the EOAT can grip reliably—should be specified with margin beyond the current product line. Designing for cases larger and heavier than anything in the current portfolio means a new product line launched after installation does not require a new EOAT.
Don't underestimate pattern management. Retailers change pallet specifications more often than most manufacturers anticipate. Having offline pattern design capability with simulation-based validation prevented production disruptions that would have eroded the throughput gains.
Validate with real product, not simulations alone. Case surface finish, label placement, and seal integrity all affect grip reliability. Several case types that gripped perfectly in testing showed issues in production due to label stock variations from different suppliers. The commissioning period should include runs with product from every active supplier.
Applying These Principles
Mixed-case palletizing represents one of the higher-complexity applications in end-of-line automation, but the core engineering principles are the same ones that apply to any palletizing and packaging automation project: define the full range of operating conditions, design for the worst case rather than the average, and invest in the material handling upstream of the robot at least as heavily as in the robot itself.
For consumer goods manufacturers dealing with SKU proliferation and labor challenges at end-of-line, robotic mixed-case palletizing has moved from an emerging technology to a proven solution. The key is rigorous upfront engineering to match the system design to the actual—not theoretical—operating requirements of the facility.
AMD Machines has designed and integrated palletizing systems across consumer goods and food and beverage applications. Contact us to discuss how mixed-case palletizing could address your end-of-line challenges.