Outer carton
Shipping carton optimisation determines which outer carton is chosen for each delivery and which items go into it. Fewer, better-filled packaging units reduce packaging, filling material and transport costs for the shipper.
Outer carton at a glance
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Shipping carton optimisation with AI
In the solution example, AIM - Agile IT Management examines whether machine learning can improve an existing packing optimisation. It is based on the AIM.packing solution, which connects to the SAP S/4HANA ERP system. It selects as few packaging units as possible for each delivery and assigns as many items as possible to them so that space is used well. It takes into account maximum weights per packaging unit, fragile items, hazardous goods and specified orientations. The optimisation goal is defined in four hierarchical levels. Statistical distributions of order structures, optimisation performance and run times were evaluated against the existing solution.
The user is FÖRCH, a wholesale supplier of products for trade and industry. FÖRCH has optimised its packaging with software for almost 20 years. When S/4HANA was introduced in 2022, the established solution was put to the test, partly because very large orders exceeded the one-second time limit for optimisation. In a three-month proof of value, benchmarks based on real order data showed that AIM.packing can save up to 3.5% of packaging. FÖRCH names lorry load space optimisation and optimising the packaging units themselves as possible next steps.
Shipping carton optimisation: frequently asked questions
What does packing optimisation for outer cartons take into account?
Besides volume, packing optimisation takes into account the weight, fragility and hazardous nature of items. In the FÖRCH and AIM example, this includes maximum weights per packaging unit, fragile items, hazardous goods and specified orientations. The software selects as few packaging units as possible and fills them as well as possible. The optimisation goal is structured in four hierarchical levels.
How does carton size optimisation reduce costs?
Software reduces packaging costs by selecting fewer, better-filled cartons for each delivery. At FÖRCH, benchmarks based on real order data showed that AIM.packing can save up to 3.5% of packaging. Less packaging also means less filling material, lower transport costs and less disposal effort for the customer. This was determined in a three-month proof of value.
How does a carton selection project run?
Such a project starts by analysing existing order and process data. At FÖRCH, AIM used a standardised approach with checklists and data analysis tools. The 'glass ceiling', an estimate of the optimisation potential based on order structures, was determined early on. The project ended with a clean measurement against the existing solution. The preliminary project took three months.
Why is classic carton fill rate optimisation often no longer enough?
Classic methods reach their time limits with large orders. At FÖRCH, very large orders exceeded the one-second limit because of the complexity of the optimisation. When SAP S/4HANA was introduced in 2022, FÖRCH therefore had it checked whether machine learning could improve the results. AIM evaluated the data and optimisation potential and laid the groundwork for AIM.packing.
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