Selecting the correct transport container has a significant impact on transportation costs and logistics efficiency. Traditional precalculation methods focus on the volume and weight of the freight and the container itself. This approach, where the objects are clearly “liquefied”, necessitates a high safety buffer (“air”) in the transport container, since most of the objects have specific dimensions and may not fit in a random combination into a container. W2MO Case Pack Optimization / 3D-Package Builder is a powerful system that considers the dimensions of the packed objects as well as the transport containers and their orientation. Sophisticated mathematical algorithms take into account numerous other restrictions such as material flow, stackability, fragility, or joint packing restrictions. The visualization of the calculated packing scheme in 3D with interactive options accelerates the packing process in practice. The result can be presented on almost any device, including tablet and PCs. Integration with the identification station allows for direct application directly at the packing station.

The W2MO Package Builder enables the creation of optimal pallets and packing schemes and can be integrated with SAP TM. When the delivery quantity in outbound becomes known, the exact pallet quantity can be determined in advance, allowing for the corresponding transport capacities to be reserved at the appropriate time. By extending the logic to inbound deliveries, the expected quantity of storage needed in the transporter and warehouse can be planned, ensuring efficient use of resources. The receiving plant, product, and supplier are all considered, ensuring efficient use of available resources.

A non-optimized case portfolio leads to high consumption of filling material, poorly-packed cartons, and a high rate of transport damages. This is often caused by a variety of different-sized shipping cartons, which are used without systematic analysis. W2MO Case Portfolio Optimization determines an optimized quantity and dimensioning of transport containers for given order scenarios. There are two calculation methods for carton and case optimization: one fully automated and the other interactive, but highly supported by algorithms. In both cases, our objective is to create the optimal conditions for the most effective order packing option and to determine the most appropriate case set. Thanks to our robust parallelization and highly efficient data structures, we can process vast amounts of data in a timely manner, allowing us to conduct comprehensive analyse over longer time periods.