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Virebox.AI machine vision solution ensures quality at Raisio

Drive for innovation brings competitive advantage to Raisioaqua

Vire Labs’ AI-based machine vision solution is an important part of the quality control system at Raisioaqua in Finland. Machine vision allows the company to ensure the high quality and uniformity of their products. 

Raisioaqua, which is a part of the Raisio group, manufactures high-quality feed for various different species of fish. The company’s customers include fish farms in Finland and in the Baltic Sea region. The European market is highly competitive, and Raisio’s strengths include high quality, an ecological approach, and innovation.

Examples of Raisioaqua’s innovations include the Baltic Blend® fish feed, which uses fish meal and oil made from Baltic Sea fish, and the Growth Sonar application, which enables fish farmers, for example, to handle feeding remotely.
“When you’re competing against bigger players, you have to be more innovative. We are constantly striving to further develop our operations,” says Plant Manager Petri Elonen from Raisioaqua.

"When you’re competing against bigger players, you have to be more innovative."

Petri Elonen, Raisioaqua

Constant monitoring of quality

The importance of innovation and digitalization is emphasized in Raisio’s own factory environment, as well. The machine vision solution developed by Vire Labs Oy is a central part of the quality assurance process. The solution collects visual product quality data during the manufacturing process and shares the information with the Siemens MindSphere IoT platform used by Raisio.

Raisioaqua strives to produce fish feed with a uniform high quality, and this requires constant monitoring. 
“In the past, visual quality control was done by human eyes. The problem with this was that people may have very differing views on what good quality actually means, and a slow decline in quality is very difficult to detect with the human eye. With the machine vision solution we are able to achieve better results. If the quality falls below a set level, the solution will immediately inform the operator that corrective measures are needed,” Petri Elonen explains.

Implemented within two months

The most significant factor that negatively affects fish feed quality is dust.
“We are constantly monitoring production quality by using the Vire Labs solution and by measuring moisture levels. If the set quality criteria are not met, we separate the batch from others and it will not be sent to customers. It does not have to be thrown away, and can instead be reused in the production process,” Elonen says.

Raisioaqua strives to produce fish feed with a uniform high quality. This requires constant monitoring, and the machine vision solution developed by Vire Labs is a central element in the quality control.

The machine vision solution is powered by the AI-based Virebox.AI device developed by Vire Labs. The system uses cameras to record a certain stage of the production process.
“The amount of dust in the product is identified from the photographs by using an algorithm developed by Vire Labs. We delivered photographic examples of different quality classifications from our production line to Vire Labs, and they taught Virebox.AI to identify any problems in just a few weeks,” Petri Elonen says. 

The AI was able to accurately identify any deviations in quality already during the pilot, and the machine vision solution was moved to production within two months. 
“We introduced the intelligent machine vision solution first on one and then on another production line. Both lines feature a Virebox.AI terminal and one camera”, explains Elonen. 

Payback in less than a year

The intelligent machine vision solution has been in use at Raisioaqua since 2019, and it is now a crucial part of Raisio’s quality control system. Petri Elonen says that using the system paid for itself in less than a year. 
“This was a good choice for us. It was evident as soon as we were able to implement the solution. If we can prevent even one customer from leaving by ensuring a good impression of our production quality, the machine vision solution has already paid for itself many times over,” says Elonen.

Raisio is currently trying to find ways to utilize machine vision more extensively in their operations. 
“Currently, we are recording a certain phase of the production process on two production lines. We are considering the possibility of expanding the machine vision solution to the bagging phase, so that the responsible person does not have to second-guess if everything is as it should be,” tells Petri Elonen. 

 

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To prevent dust related problems and to make maintenance easy, the cameras have been installed in a sealed box which is separated from the production line with a glass window.
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The Virebox.AI terminal analyses the image data coming from the cameras and sends the quality information instantly to the ioT system.

"If we can prevent even one customer from leaving by ensuring a good impression of our production quality, the machine vision solution has already paid for itself many times over.”

Petri Elonen, Raisioaqua

The importance of networking and references

It is common that companies know what they need in order to improve their own processes, but lack the resources to resolve the situation on their own. Sometimes it may be hard to find the right partner who can provide a functional solution. 

Petri Elonen found Vire Labs through his own networks. 
“Networking and references are very important in today’s world. You cannot always know where to find the best partners to help your company develop its operations further. I heard about Vire Labs on Aalto University’s IoT course from a fellow attendee who had collaborated with Vire Labs. That was a really good tip,” Petri Elonen says, smiling.    

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