
製品の寸法を特定するために、動的な視覚スキャンを開始する。
混在するSKU(商品)の統合における最適な負荷パターンを計算する。
多様なサイズの段ボールを掴むために、適応型のグリッパーを導入する。
標準的なパレット構造に、正確な位置に配置する。
サイクル完了前に構造的な安定性を検証する。

Validate site conditions, network latency, and safety protocols prior to system activation.
Conduct comprehensive site survey to verify floor space and load-bearing capacity.
Ensure industrial-grade network stability for real-time data transmission.
Confirm all safety standards and emergency stop protocols are met.
Gather detailed SKU dimensions and weight data for AI training models.
Verify power availability and redundancy requirements for continuous operation.
Validate aisle widths and pallet positioning accuracy against system constraints.
Initiate small-scale pilot run to validate SKU recognition and cycle times.
Integrate with existing WMS and optimize AI models for specific product mix.
Roll out across all production lines and monitor KPIs for sustained performance.
98%の最大負荷密度を達成。
サブミリメートルレベルの精度を維持します。
Utilize 3D vision to identify SKU variations in real-time.
Select collaborative arms with high payload capacity for palletizing tasks.
Deploy soft grippers capable of handling diverse packaging materials securely.
Process data locally to ensure low latency and robust decision-making.
Prepare workforce for new workflows through targeted training programs.
Establish routine calibration schedules to maintain accuracy over time.
Keep SKU database updated with new products and packaging changes.
Define clear escalation paths for technical support and maintenance issues.