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DNV launches next generation of Steel Load Planner with built-in AI cargo optimization in International Shipping News 03/06/2026 Classification society DNV released version 2 of its award-winning Steel Load Planner (SLP V2.0) self-service application at the Posidonia trade fair this week. Building on two years of operational experience, the new version can automatically generate fully AI optimized loading plans with a structural assessment in under five minutes. Its application has also been extended beyond the bulk carrier segment, bringing automated coil planning to general cargo and multi-purpose vessels for the first time. Steel coils are one of the staple minor-bulk cargoes, yet remain among the most demanding to plan, with wide variations in coil size, weight and behaviour during stowage. At the same time, tight tonnage supply, a shortage of newbuild slots, and growing regulatory costs for emissions, mean owners and operators need to maximize the loading capacity of their existing vessels to remain competitive. Building on the original Steel Load Planner, which launched in 2023 and won the IT Solution award at the International Bulk Journal Awards, DNV’s SLP V2.0 can now automate planning work that previously relied on manual input and judgement. This means that even non-specialists can be guided by the built-in AI and produce a fully optimized plan in just minutes. Planners enter the vessel and the coil dimensions, and SLP V2 identifies the stronger and weaker areas of the structure, then optimizes dunnage as well as coil placement accordingly and generates a loading plan. In addition, general cargo ships and multi-purpose vessels can now take advantage of the same automated structural assessments. Morten Løvstad, Vice President and Global Business Director for Bulk Carriers, DNV Maritime, said: “When we launched Steel Load Planner, we had great feedback, but the real test would be how it performed for our customers. Now over two years later and with more tha
DNV launches next generation of Steel Load Planner with built-in AI cargo optimization
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