DecisionTower™ with FillPak Trident™ or FillPak® SL

Automated paper-based void filling with AI vision technology. Automated void filling can speed up the packaging process, increase throughput, and ensure the right amount of protection is used in the boxes.

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DecisionTower with FillPak Trident or FillPak® SL

 

Automated paper-based void filling with AI vision technology

Automated void filling can speed up the packaging process, increase throughput, and ensure the right amount of protection is used in the boxes. Too little void-fill material means damaged products. Too much affects both costs and the environment – and impacts the all-important unboxing experience.

 
 
Bringing two Ranpak solutions together into one capable system, the Ranpak DecisionTower combined with our FillPak Trident™ or FillPak® SL paper converter measures the amount of void in each box and dispenses the precise amount of required paper-based void fill material for every individual parcel.
 
 
As a vision-based and semi-automated end-of-line solution, it provides unrivaled ROI through better operator efficiency, lower use of consumables, enhanced sustainability, and an improved unboxing experience.
 
 

Key benefits

Improved packaging efficiency

  • DecisionTower with FillPak Trident/FillPak SL is a semi-automated solution, improving results end-to-end.
  • Every single box dispatched contains the optimal amount of void-fill paper.
  • Up to 35% paper reduction is due to the combination of triangle-shaped paper pads and vision-based analysis of paper usage.
  • Damage rates from underfilling are cut dramatically, resulting in fewer returns and improved quality.

Sustainable materials

  • An end to overfilling benefits the environment.
  • Customers value fully curbside recyclable paper packaging material.
  • Ambitious sustainability targets are more easily achieved.

High-tech and easy to use

  • Sophisticated, vision-enabled AI technology copes with any box size, is easy to use, and provides data collection.
  • Limited-to-no operator training required.