Multi-purchase packaging. It’s a big deal for online retailers. How can they maximise the packing of various irregular shaped objects and reduce the amount of empty box space, yet deliver the goods in optimum condition?
A new dimensioner system developed in the US might have the answer. The Cubiscan combines an infrared scanner and multiple load cells to accurately capture the weight and dimensions of any object, from lightweight poly-bagged clothing to paint rollers and ski poles.
Scan, store, ship
The unit is primarily being marketed for use in warehouses at the point where goods arrive. By scanning each object and storing the data on arrival, when the item is to be dispatched to a customer, the warehouse management system can instruct the packing team in the optimum size of packing box required. The data can also be used to maximise storage space in the warehouse, and also to create bespoke packaging via a on-demand box-maker if required.
The manufacturers reckon that the high level of accuracy achieved by the infra red/load cell combination can save companies up to 25% in DIM (dimensional weight) carrier charges. Equally, it reduces packaging waste and reduces fuel costs due to inefficient loading.
So, thanks to load cells, home deliveries of large cardboard boxes containing a couple of items and an awful lot of air might be consigned to history.
Load cells: the bigger picture
Load cells have been in daily use in factories around the world, ensuring accurate measurements in weighing, grading & sorting, and filling and bagging machines for many years. What has changed over the years is the ability for these load cells to interface with systems, often wirelessly, capturing and displaying data in real time.
It’s all part of the big data revolution, where data can be collected and stored quickly, easily and with minimal costs. The real revolution is in how this data is analysed. Instead of taking sample readings and extrapolating, big data allows companies to take almost continual feedback on processes, and then spot patterns that deviate from the norm. This allows manufacturers to spot issues with machinery and precesses before a breakdown or failure, and to implement predictive maintenance by using normal operation data.
We’ll be covering the possible impacts of big data from load cells in our next blog – stay tuned!