How Aurai’s Data-Driven Solutions Protect Ships
We collaborate with partners of all shapes and sizes: from banks, insurance companies and marketing specialists to the Dutch government and publishing houses. Each project brings a new collaborator, but Aurai's goal remains the same: to make the possibilities of innovative technology useful for organizations.One of our latest success stories is our collaboration with Cordstrap, a multinational with Dutch roots that specializes in keeping the world’s Cargo safe. For their 'Cargo Monitoring Data' project, our Data Scientist developed models that optimize risk analyses, which enable Cordstrap to better monitor and protect their customers' cargo.
To optimize cooperation between Aurai and Cordstrap, we started with jointly defining the key issue at hand: how can data play a role in the safe transportation of cargo on ships? To arrive in one piece, cargo ships and their containers endeavor extreme weather conditions, ranging from high waves and sea storms to heavy downpours. Preventing water damage and moisture is particularly essential because it can have major consequences for different types of cargo, making its prevention essential. The main goal of the Cargo Monitoring Data-project was to investigate whether data-driven solutions can minimize the risk of water damage, for example, by providing insight into the risks of specific shipping routes and weather conditions, and showing live updates of the climate within the container.
Running a Tight Ship From Home
Shortly after our Data Scientist joined the project, the corona pandemic changed the world. Suddenly, we had to develop our data-driven solutions from home. This new way of working took some getting used to. “The sudden shift to working from home presented a challenge. Fortunately, by that time I was used to collaborating online: because of Cordstrap’s international focus, much of our communication was being carried out digitally anyway.”
Some of our challenges included managing the client’s expectations, the quality and quantity of data and how to present a comprehensible picture of the technical data solutions to all stakeholders. : “Many of our partners find the technical descriptions and jargon that us Data Scientists use every day difficult to understand. In order to communicate effectively with all stakeholders, I drew on Aurai’s courses on the art of storytelling and methodologies for inclusion. This, combined with the helpful feedback from Cordstrap, helped me communicate clear and simple information and presentations to all parties involved.”
Testing the Waters
After defining the question and shared objectives, we got to work on analyzing archival data from Cordstrap. “I was responsible for redesigning and cleaning up the visual data sets used for risk reporting.” It turned out to be a time-consuming process that required patience and an eye for detail, but once analyzed, the historical data provided a good picture of all the risk factors. Mold was one of the most worrying risk factors. In order to clarify exactly when water damage occurs, we investigated, among other factors, at what moisture saturation and after how long the mold begins to develop. Aurai’s consultant Stefan: “I was very impressed with the speed and extent to which you were able to master what was completely new information for you. You quickly became an expert in the field of moisture damage in sea transport.”
In addition to examining mold growth, we also analyzed other risk factors. : “Many interesting phenomena can occur inside the containers in transit. ‘Container rain’ is one of them. Ships often cover vast distances and travel through multiple climate zones. As a result, they are exposed to large temperature differences, which can cause condensation. It is the same process that causes the small drops of water that start to form after you take a cold beer from the fridge. A similar process can occur in containers, but so vigorously that it appears to be raining inside due to condensation dripping from the ceiling. When transporting electronics, that’s, of course, far from ideal.”
Developing a Proof of Concept
After completing his research and analyses, we worked on developing more detailed visual representations of maritime routes, which provides Cordstrap comprehensive insight into the risks that cargo ships face throughout the year. He then moved on to work on the realization of the Proof of Concept: building accurate data models that help predict the risk of moisture damage affecting the products on board. The purpose of these models was not only to give Cordstrap the opportunity to monitor their ships and products in realtime, but also to give them the opportunity to take timely measures if necessary to secure their cargo. Their latest product, ‘moisture control’, plays an important role in this by preventing excess humidity through regulating the moisture content in containers.
The results of the data models and new, more detailed risk reports are promising. “the short-term forecast is now particularly accurate.” These accurate short-term forecasts give Cordstrap more insight into and control over the condition of the cargo while in transit – and the value of future, accurate long-term insights is evident. “we are proud of having shared the value of data science in solving problems, and showing how data technology can improve decision-making processes. This goes way beyond predicting the risk of moisture damage: data science can offer business solutions to all sorts of problems.”
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