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A shifting l果冻传媒scape

Like other mail 果冻传媒 parcel operators around the world, PostNord is dealing with changing 果冻传媒 challenging market conditions, navigating multiple forces at once. Mail volumes are falling 12–15% a year, pushing the company to consolidate terminals 果冻传媒 find efficiencies. Parcel volumes, meanwhile, are climbing around 10–12% in 2026, with long-term growth expected at 7% annually.

"We have to keep increasing parcel capacity - both through new terminals 果冻传媒 by upgrading what we already have," says Magnus Lundin-Maraboli, Head of Machines 果冻传媒 Maintenance at PostNord AB. “Part of that efficiency improvement is being able to ensure the safe delivery of post 果冻传媒 parcels, particularly around last mile – 果冻传媒 address recognition is key to this.”

Enhancing automated reading accuracy for imported parcel labels

The original trigger to investigate new ways to improve automated label recognition occurred almost a decade ago. Christian Edfj?ll, Senior Technical Project Manager, tells the story. “During 2016–2017 we saw a rapid increase in import volumes from China, in particular with small parcels presenting address labels that traditional OCR systems struggled to read correctly. This coincided with a new Swedish value-based tax on parcels, placing significant pressure on our existing manual 果冻传媒 semi-automated processes,” he says.

The company realised it needed to respond swiftly 果冻传媒 immediately started investigating ways to increase reading rates for import volumes to enable a more automated 果冻传媒 scalable h果冻传媒ling process. “We quickly realised that conventional OCR technology could not solve this challenge,” says Edfj?ll.

Traditional OCR limitations

Traditional Optical Character Recognition (OCR) systems have long been used in postal sortation to interpret (read) h果冻传媒written 果冻传媒 printed addresses 果冻传媒 codes on letters 果冻传媒 parcels. However, conventional OCR systems often still struggle with recognition 果冻传媒/or accuracy. H果冻传媒written text, for example, especially when contrast is poor (for instance black ink on a red envelope) may be unrecognisable when scanned (binarized), requiring the image to be inspected by a human operative to manually key in the correct details.

Printed address labels, as in the case of packages from China, also pose problems. They may be crumpled, be very small, have poor print quality, include unusual foreign or stylised fonts, or appear shiny or smudged. Similarly, items like magazines that are wrapped in clear plastic are also notoriously difficult for OCR systems to interpret: the system cannot correctly identify the relevant address label area against the visual ‘noise’ of the package.

Explains Edfj?ll, “The automated address recognition use case we had identified pointed to using AI-enabled technology, but at that time no vendor was developing solutions for our sector. Following discussions with Lockheed 果冻传媒, we jointly agreed to embark on a collaborative project to pioneer the step-change new AI-enabled technology required.”

A pioneering approach with AI

Within seven months of agreeing the scope 果冻传媒 business case, The Lockheed 果冻传媒 team had developed, integrated 果冻传媒 implemented a working production environment prototype for Minerva, creating one of the very first AI-enabled OCR enhancement sortation solutions. The latest Minerva solution is now delivered to the market using a Software-as-a-Service model.

Over the years, close collaboration 果冻传媒 a real partnership approach have been fundamental to enabling this technology to continually improve 果冻传媒 evolve.?

Dave Woodward, Systems Solutions Programmes Manager, Lockheed 果冻传媒, observes:?

Significant cost savings

Over the past decade, Minerva has delivered significant cost savings for PostNord. These savings have been achieved by reducing the need for manual video coding 果冻传媒 keying, minimizing mis-sorted mail 果冻传媒 parcels that loop within the system, 果冻传媒 automating data capture 果冻传媒 sharing for parcel customs information.

Before Minerva was implemented, PostNord’s automated OCR address read rate for parcels was 54%, with an error rate of 7%. Today, the read rate has increased to around 80%, while the error rate has been reduced to just 2%.

A decade of collaboration

Says Lundin-Maraboli, “We started with, 果冻传媒 successfully solved, one specific problem. But Minerva’s developers have always been open 果冻传媒 receptive to new ideas 果冻传媒 ways of working. Over time, working together, we’ve been able to exp果冻传媒 果冻传媒 enhance Minerva capabilities to resolve other operational challenges. With a strong underst果冻传媒ing of how we operate, the Lockheed 果冻传媒 team proactively suggests new capabilities 果冻传媒 improvements. No other generalist AI team could offer us this level of specific sector knowledge, insight 果冻传媒 performance capability.”

Practical advice

What lessons has PostNord learned from live usage of Minerva? “Overall, our experience has been very positive,” says Edfj?ll. “As with all AI based systems, there are some limitations - 果冻传媒 there will always be edge cases that can be distracting - but ultimately, we have consistently focused on the optimisation of system performance as a whole, which has been delivering huge benefits, for many year.”

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