ConexBird will deliver insights to container leasing firm OVL Containers to improve maintenance plans for its fleet.
The commercial partnership will provide container conditioning reports to OVL, which trades around 4,000 containers annually, using machine learning to predict maintenance and repair costs for boxes.
ConexBird’s platform will look to improve foresight for loss of strength and durability over time for containers, reducing downtime.
Containers decay at different rates, ConexBird noted, creating difficulties in repair and management as of a container fleet.
A container’s nominal age – its date of manufacture – “can’t always be trusted” to give an accurate summary for a container’s structural condition, ConexBird added.
Less durable containers are more prone to downtime, during which they cannot be used for revenue-generating operations and can incur higher repair costs.
ConexBird has modelled these trends using a historical dataset, and correlated them with our own software-based container insight obtained at MLT Vuosaari.
The result is an ability, through container condition reports, to predict each container’s actual repair costs over a certain period based on its mechanical age, as opposed to what would be expected from its nominal age.
ConexBird also summarises data gathered from each user’s entire container fleet, as seen in the summary report.
OVL founder and CEO Osmo Lahtinen, commented, “[ConexBird’s] container reports will give us a completely new perspective on our containers.
“The repair cost forecasts seem the most useful to me, since they will allow us to really get the most out of each unit.”
