tiny ml as key technology
Last year, Techport together with Hilton Foods Holland successfully completed the first use case Tiny Machine Learning. With Tiny Machine Learning, energy consumption and the production process can be mapped, resulting in energy savings of up to 30%. Jeroen Reiber of Hilton Foods talks about the successful collaboration as part of Techport's 10th anniversary.
reducing food waste
Jeroen: “About two years ago, I came into contact with André Gerver from Techport through a colleague. We share the same passion for innovation. Soon we came up with the idea of setting up a use case with Tiny ML together with two students. This technology allows you to run predictions on the device itself (on the edge). It is safe, cheaper and faster(er) than current solutions where you first have to invest a long period of time in collecting data and storing it in the cloud. Only after a long time can you then draw conclusions from that data.”
He continues: “With Tiny ML, this process is much faster because no data transfer is required. We researched one of our production machines in this way to predict maintenance and thus prevent failure or downtime, which in turn reduces food waste. One student demonstrated the technical feasibility. The other student worked out the strategic implication of Smart Industry for the entire organisation and the business case.”
develop from user needs
“As a true techie, I want the basics to be in order, but also look at how digitalisation can help our company, our employees and our customers further. We supply meat to the Netherlands” largest grocer. Every year, we want to do it a bit faster, better and cheaper. Growing together and getting better, that's the goal."
Jeroen sees Steve Jobs as his great inspiration: “Jobs developed products from the needs of users, not the other way around. This is also how we apply Tiny Machine Learning. What does it benefit our employee? And our customer? And ourselves? We use data to predict maintenance, so we can prevent problems even before they occur. You want to prevent machines from stalling, people from not being able to work and meat from not being processed. I find it a challenge to make all the information we get from such a machine understandable. Not only for our management, but also for the people who operate the machines, for example the operators. That they too understand what they are looking at. That way, for them, the user experience also improves.”
The mission? to implement Tiny Machine Learning throughout Hilton Foods. The initial results were convincing, giving the management the green light for the next step to monitor an entire production line in the same way.
Jeroen Reiber - Hilton Foods Holland
still relatively unknown, but full of potential
Tiny Machine Learning is still relatively unknown, but offers a lot of potential for businesses. Especially for SMEs because it is affordable.
Jeroen is enthusiastic about the cooperation with Techport: “They have been incredibly good at thinking with us about setting up the studies and working out the business case. It is a low-threshold way to innovate without large investments or risks. You can get started with just a few hundred euros in hardware costs. Right now, there is too little (correct) data and the quality is insufficient and the solutions are too expensive to make real strides with predictive maintenance. Tiny ML is going to enable and accelerate the successful deployment of predictive maintenance. It is rightly seen as a key technology.”