Sony — Smart Warehouse Automation

Challenges

• Manual item searching was time-consuming, slowing down production line supply
• Inventory accuracy was difficult to maintain with manual processes
• High physical demands on warehouse workers handling repetitive tasks
• Insufficient storage density in the existing 3,400 m² facility — a constraint that Li-Ning solved with 48,160 bin positions in their 50,000 m² warehouse
• Need for a system that integrates seamlessly with Sony’s existing workflows

Solution

• Latent Jacking Robots: 38 picking robots and 11 transport robots working in coordinated multi-robot collaboration with optimized path planning
• High-Density Racking: Custom shelf layouts designed to maximize space utilization and order response speed
• “One Person, Dual Workstation” Design: Since each order takes ~1.5 minutes to process, a single operator works across two stations, keeping robots utilized and eliminating idle time
• WES Integration: Custom-developed Warehouse Execution System deeply integrated with Sony’s existing processes for smooth transition and data continuity
• Custom Workstations: Ergonomically designed stations optimized for small camera lens components, with specialized small-bin shelf structures for precision storage

Results

• Inventory accuracy improved dramatically with real-time digital tracking
• Item search time reduced significantly — robots bring goods to operators
• Worker physical strain substantially decreased through automation
• Storage density optimized within the same 3,400 m² footprint
• Phase 2 expansion already launched, extending robot coverage deeper into the raw material warehouse

In the same 3C electronics sector, Konica Minolta achieved a 92% reduction in inventory checks through a similar goods-to-person approach.

When a single dropped tote can destroy thousands of dollars in product, the automation system cannot afford a learning curve.

The Cost of Damage in Consumer Electronics

A scratched phone screen is scrap. A dented laptop chassis goes to the refurbishment channel at a fraction of retail price. A cracked camera lens assembly has zero salvage value. In Sony’s logistics operation, the financial penalty for handling damage is not a rounding error — it is a line item that procurement and finance track monthly.

Manual warehouses control damage through training and supervision. Experienced pickers handle fragile items carefully; new hires learn through mistakes that cost money. During peak seasons when temporary staff fill the floor, damage rates spike predictably. The correlation between workforce experience and product damage is well-documented across the electronics industry.

Sony’s 49-robot deployment removes that variable entirely. Every retrieval, transport, and delivery cycle executes with the same acceleration profile, the same vibration envelope, and the same placement precision — whether it is the first pick of the day or the ten-thousandth. The WES assigns handling parameters by product category, so a tote of wireless earbuds travels at different speeds and deceleration rates than a tote of gaming consoles.

Why 49 Robots Instead of 20 or 80

Fleet sizing is one of the most consequential decisions in warehouse automation. Too few robots create bottlenecks during peak hours. Too many robots create traffic congestion that slows the entire fleet below the throughput of a smaller one.

The 49-robot count at Sony came from simulation modeling that balanced three constraints: peak throughput requirements (orders per hour during the busiest shipping windows), aisle density limits (maximum robots per corridor before congestion degrades performance), and redundancy margin (the fleet must maintain target throughput with 10-15% of robots offline for charging or maintenance).

In our experience, the optimal fleet size is rarely what clients expect. Operations teams accustomed to “more people = more throughput” assume the same applies to robots. It does — up to a point. Beyond that point, the WES spends more time managing traffic conflicts than executing picks. The simulation phase before deployment is where we identify that inflection point for each facility’s specific layout and order profile.

Protecting High-Value Inventory Through System Design

Zero-damage handling is not a single feature. It is a design philosophy applied across every component of the system.

Storage: totes use custom inserts molded to product dimensions, preventing items from shifting during transport. The hardware systems include shock-absorbing mounts on conveyor transfer points where totes change direction or elevation.

Transport: robots maintain speed profiles calibrated to the fragility classification of their current payload. A robot carrying optical equipment moves differently than one carrying cable accessories — same robot, different motion parameters loaded from the WES at task assignment.

Handoff: the transition points where totes move between robots, conveyors, and picking stations are the highest-risk moments. Each handoff uses guided alignment mechanisms that eliminate the bump-and-settle approach common in less sensitive operations.

For electronics manufacturers and distributors evaluating similar requirements, the solutions page covers how we scope projects where product protection is the primary design driver. The SICC case shows comparable precision handling for semiconductor wafers. Our goods-to-person picking guide explains the station design considerations for high-value item workflows.

Frequently Asked Questions

How does the system handle mixed-fragility orders where robust and fragile items ship together?

The WES sequences picks so fragile items arrive at the packing station last, placing them on top of the carton. Pack instructions displayed to the operator specify cushioning requirements by item. For orders combining heavy items (power supplies, speakers) with fragile items (screens, lenses), the system may split into separate cartons automatically based on weight and fragility rules configured per product category.

What maintenance schedule keeps 49 robots running without throughput drops?

Robots rotate through maintenance on a staggered schedule managed by the WES. At any given time, 2-4 robots are in the charging and maintenance bay while the remaining fleet covers full throughput. Predictive monitoring tracks motor temperatures, wheel wear, battery degradation, and sensor calibration drift — flagging robots for service before performance degrades. The types of ASRS systems page covers how different robot architectures affect maintenance planning.

Is the zero-damage standard achievable for products with irregular shapes or flexible packaging?

Rigid, consistently shaped products like Sony’s electronics are the strongest candidates. Products with irregular shapes or soft packaging — plush toys, bagged items, oddly shaped accessories — require custom tote inserts or different picking approaches. Damage rates below 0.01% are achievable for rigid electronics; flexible or irregular items typically land in the 0.05-0.1% range with current technology. Contact our team for a product-mix assessment.