Haemill Logics

Haemill Logics, a South Korean third-party logistics provider based in Icheon serving online retailers, fashion brands, and large-scale retailers since 2014, found its traditional warehouse operations increasingly untenable as e-commerce volumes grew. Peak shopping events such as Black Friday caused order volumes to surge up to four times the normal rate, exposing the hard limits of manual picking: space constraints prevented efficient inventory storage, stock visibility was unreliable, and throughput depended heavily on worker skill level. These bottlenecks degraded order-fulfillment speed and accuracy at precisely the moments when customer expectations were highest, directly threatening client retention and profitability.

Haemill partnered with Asetec, AutoStore's regional implementation partner, to deploy a grid-based robotic warehouse system in a brownfield installation within its existing facility. The system comprises 8 R5 Robots, 2 CarouselPorts, 1 ConveyorPort, and 6,079 storage bins — robots autonomously retrieve bins from the grid and deliver them to operator workstations, eliminating the need for pickers to traverse warehouse aisles. The robotic process automation layer integrated directly with Haemill's existing NEXOS WMS, enabling real-time inventory visibility without replacing core systems. The modular grid design was chosen specifically for its scalability, allowing future capacity expansion without operational disruption or significant additional floor space.

The AutoStore deployment delivered measurable gains across every operational dimension Haemill targeted. The headline outcome was a 4x increase in storage capacity within the same physical footprint — the same inventory now occupies just a quarter of its prior space. Additional outcomes include:

• 30% improvement in profitability from combined labor and space efficiency gains
• 15% revenue increase, attributed to improved service levels and throughput
• 25% rise in orders processed, demonstrating throughput scalability under peak load
• 10% reduction in picking errors, improving customer satisfaction
• Employee daily steps reduced from 20,000 to 8,000, improving worker well-being and retention

New hires now reach high productivity with minimal training, reducing the skill-dependency that previously created staffing risk during peak seasons.

• Grid-based robotic storage can quadruple warehouse density within an existing footprint, making it a compelling option for space-constrained 3PLs before committing to facility expansion.
• Brownfield installations are viable: AutoStore integrated with Haemill's existing NEXOS WMS without replacing core systems, reducing deployment risk.
• Automating the pick path decouples throughput from headcount and skill level — critical for operations where peak demand is unpredictable and onboarding time is a bottleneck.
• ROI compounds across multiple vectors: space savings, labor efficiency, error reduction, and customer satisfaction all contribute, so evaluation should model all four rather than labor cost alone.
• Plan for expansion from day one — the modular design enabled Haemill to target a 50%+ further capacity increase post-deployment.