Warehouse Operations Optimization

AI analyzes warehouse work and generates work orders to improve picking, packing, and item collection efficiency.

Business impact

• Work time — Hitachi reported an 8% decrease in work time when comparing the warehouse system with the AI technology against the version without it.
• Item collection efficiency — Hitachi measured item collection efficiency in the distribution warehouse demonstration.

Data requirements

• Warehouse video footage (image) — Panasonic uses video analysis of picking and packing operations.
• Work details and work results (tabular) — Hitachi analyzes daily business-system data about work details and results.
• Work volume (tabular) — Hitachi uses work volume data to match instructions to current conditions.
• Demand data (tabular) — Hitachi uses demand fluctuation data to adjust work orders.
• Weather data (tabular) — Hitachi selects data similar to actual work conditions, including weather, when generating instructions.

AI methods and techniques

• Video analysis — Panasonic uses AI video analysis to break warehouse work into tasks and inspect picking and packing operations.
• Demand-pattern analysis — Hitachi's AI analyzes demand fluctuation to produce appropriate work orders.
• Kaizen-aware work-order generation — Hitachi applies on-site improvement activity and worker ideas to the next work instructions.
• Big data analysis — Hitachi derives work guidance from big data accumulated daily in business systems.

Industries

Real-world evidence

3 documented case studies on record.

Companies using this: Panasonic, Hitachi, Symbotic.