Intelligent ULD Build-up
系统价值和业务痛点

1. Maximize ULD space utilization and increase flight cargo revenue: The built-in intelligent build-up algorithm computes the optimal placement scheme considering cargo dimensions, weight, loading priority, and multiple constraints such as “heavy over light / large over small”; it precisely estimates the number of pallets / containers required and reduces wasted ULD volume. Under the same capacity, more cargo can be carried — fully releasing flight capacity value and increasing per-flight cargo revenue.

2. Standardize on-site build-up operations, reducing errors and cargo damage risk: 3D visualized loading diagrams guide ground staff to place cargo correctly and unify build-up standards across stations. This prevents problems caused by experience-based manual build-up such as non-compliant stacking, crushing of fragile cargo, and inverted special cargo — reducing cargo damage and misloading incidents, and lowering claim and rework costs.

3. Simplify training and reduce reliance on experienced staff: Removes dependence on veteran build-up staff; new employees can get up to speed quickly with the system’s visualized schemes. No repeated manual calculation of pallet / container mix is needed — greatly shortening build-up planning time, reducing ground staffing and long-term training costs, and fitting multi-station scaled operations.

4. Connect upstream / downstream data flows: Standardized interfaces seamlessly integrate with booking, Weight & Balance, and cargo terminal systems; build-up details flow automatically without re-entry or paper transfer; standardized CBA supporting data is output uniformly — raising automation across cargo sales, load planning, and ground handling.

1. Maximize ULD space utilization and increase flight cargo revenue: The built-in intelligent build-up algorithm computes the optimal placement scheme considering cargo dimensions, weight, loading priority, and multiple constraints such as “heavy over light / large over small”; it precisely estimates the number of pallets / containers required and reduces wasted ULD volume. Under the same capacity, more cargo can be carried — fully releasing flight capacity value and increasing per-flight cargo revenue. <><>2. Standardize on-site build-up operations, reducing errors and cargo damage risk: 3D visualized loading diagrams guide ground staff to place cargo correctly and unify build-up standards across stations. This prevents problems caused by experience-based manual build-up such as non-compliant stacking, crushing of fragile cargo, and inverted special cargo — reducing cargo damage and misloading incidents, and lowering claim and rework costs. <><>3. Simplify training and reduce reliance on experienced staff: Removes dependence on veteran build-up staff; new employees can get up to speed quickly with the system’s visualized schemes. No repeated manual calculation of pallet / container mix is needed — greatly shortening build-up planning time, reducing ground staffing and long-term training costs, and fitting multi-station scaled operations. <><>4. Connect upstream / downstream data flows: Standardized interfaces seamlessly integrate with booking, Weight & Balance, and cargo terminal systems; build-up details flow automatically without re-entry or paper transfer; standardized CBA supporting data is output uniformly — raising automation across cargo sales, load planning, and ground handling.

功能列表
  • Cargo Data

    Cargo data: dimensions, weight, pieces, whether palletized, non-invertible, loading priority

    ULD data: ULD type, ULD quantity

  • Result Output

    Build-up result output (number of built-up ULDs, remaining cargo quantity)

    3D visualization of each ULD

    Step-by-step build-up guidance

  • Data Settings

    Cargo ULD (compartment) model data: container shape, segmented volume, internal structure — e.g., standard cuboid, shaped containers, and built-in partitions

    Aircraft type data and cargo data: cargo type, cargo dimensions, rotation reference axis, cargo weight, and orientation requirements

    Constraints: heavy-over-light, overlapping placement, large-over-small, and same-type ordering

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