Heat exchangers are not something that ordinary people encounter in their everyday lives. But it is something that is everywhere and that fulfills a great function to save heat and energy. Researchers believe that streamlining heat exchange can reduce carbon dioxide emissions by two percent and open doors for further technical solutions.

Anders Nyander works with technical development at the global company Alfa Laval and has, together with the sensor technology supplier FLIR and the startup company Ekkono, started a streamlining where they face the future of heat exchange.

– We are making a change in technology where more and more is being digitized and driven by computer control. As a large company, you may be required to experiment a bit and let go of the classic work idea. It is also important to be clever and agile in new projects to develop. Our collaboration with FLIR and Ekkono means that we can break new ground and make technical improvements in heat exchange, says Anders Nyander.

Sensor technology company FLIR develops thermal imaging cameras used for thermography, which serves as an important analysis tool for heat exchangers. The cameras see the heat on the surface of an object. Katrin Strandemar is head of technology and innovation at the company and she describes how they work to add technical expertise around IR technology in the project.

– Our collaboration is like an ecosystem where we can add intelligence. We work in different industries and are experts in different areas. FLIR has IR camera technology that is very powerful and generates data to build analyzes on in this project, says Katrin Strandemar.

The third company that is part of the collaboration to develop and improve heat exchangers is Ekkono Solutions, a company that works with artificial intelligence, more specifically machine learning and how machines themselves can register and understand data. Anders Alneng is a co-founder of Ekkono and talks about the unique benefits of their software.

– We do machine learning for existing products, where one of our strengths is sensor-based, self-learning algorithms that understand how each specific machine behaves. For example, we can calculate how dirty a heat exchanger is, which makes it easier to understand when it needs maintenance. It is a symbiosis based on converting data into actual individual algorithms for each machine.

The development of self-learning algorithms for heat exchangers is in full swing. Despite the companies’ different sizes, there is a rewarding collaboration that takes each of the companies forward.

– I generally think that the whole world is heading into a situation where you have to cooperate. It does not matter if you are a large company, you are still not big enough to be completely yourself, says Katrin Strandemar.

– For us, it is a challenge to get access to the right data. How to validate that the results you have are correct. We must get help from those who can and we have definitely received that, Anders Nyander continues at Alfa Laval.

The three companies conduct fundamentally different activities and have completely different conditions. Alfa Laval’s heat exchangers with FLIR’s thermography and Ekkono’s machine learning are moving into the future by creating self-learning algorithms for analysis and monitoring of heat exchangers. A success for the industry where machines optimize service, increase efficiency and in the long run reduce the climate footprint. With expertise in different areas, it is possible to create new innovations together. Something that is needed now more than before.

The maintenance fair is a cross-industry forum where different innovations, technologies and experiences are shared between actors in all stages of the maintenance chain. The maintenance fair is the largest and fastest growing meeting place in Europe and will take place at the Swedish Fair in Gothenburg March 15-18, 2022.