Archive April 15, 2020

Calejo is preparing for an international patent application

In addition to its Swedish patent application, Calejo Industrial Intelligence has now also submitted a PCT for an international patent application,

– In parallel, we are also preparing for several international patent filings, says Leonard Johard, CTO at Calejo.

At a so-called PCT (Patent Cooperation Treaty), an international search and patent review of the PRV (Patent and Registration Office) is carried out together with an assessment based on news value, innovation level and industrial usability.

Calejo’s previous patent application, which is currently being finalized by PRV, concerns Calejo’s unique AI engine for modeling and Reinforcement Learning. The technology allows for flexible, scalable process optimization and efficient interaction between people, data and AI.

Successful test of AI-model for energy optimization

In a recently completed Vinnova- and PiiA-funded project, SCA together with Calejo Industrial Intelligence has managed to gain a better understanding and more accurate forecast of the use of water vapor. The project has the potential to lead to a more even energy consumption over time and a significantly reduced consumption of fossil fuel in SCA Obbola site outside Umeå. The result shows the great potential of using AI in industry.

In SCA’s sulphate pulp mill in Obbola, water vapor is both a residual product and something used in the production process by, among other things, operating a turbine generator for electricity production. Usually there is a balance between need and supply of water vapor, but in case of disruptions in parts of production, a deficit of water vapor may occur. The imbalance that then arises can be regulated by either a reduction in electricity production or by creating water vapor through the combustion of fossil fuels. The latter is not very desirable.

Against this background, this Vinnova project produced an accurate forecast of the process’s need for water vapor, as well as a digital twin over the process. The goal was to be able to understand how water vapor can be created in good time before the need arises – through a better understanding of the process – without reducing electricity production or burning fossil fuels.

Impressive results

The project shows that it is theoretically possible to reduce oil consumption in the bark boilers by means of self-learning AI technology and more accurate forecasts through a changed control of the soda boiler, the cookery and the bark boiler.

“This technology is applicable in several areas, but the just completed project is one of the few where the AI technology has been successfully tested in the global process industry,” says Johannes Holmberg, CEO of Calejo Industrial Intelligence.

The model proves to be able to predict about 70 percent of the occasions when oil is used in the bark boilers. With an improved analysis and understanding of the process, a large part of the remaining 30 per cent can be eliminated.

“An optimization of the entire time period confirms the theory that it is possible to use energy in the process, so that the need for oil is greatly reduced. The 70 percent oil demand in the bark boilers, as the model can predict, will disappear completely after optimization. In addition, the evaluation clearly shows that the remaining 30 per cent of the oil consumption has occurred in addition to normal operation. This proves our original theory that steam can be produced without the addition of fossil oil in normal operation”, says Johannes Holmberg.

Several new projects are planned

The digital twin used in this project has been built entirely from a black box model, which means that it consists solely of neural networks that are trained on historical process data.

In the future, the model can also advantageously be converted to a so-called gray box model, that is, a model consisting of both trained neural networks and mathematical calculations. This will create an even better model understanding between direct and indirect process events, which will further increase the accuracy without the need for more data. A next step that is now being discussed is to test to using the model in order to provide operators with a better process support.

“A model that can predict and give indications on how the process should be managed is, from a productivity perspective, clearly interesting to us as plant owners. We are very pleased with the results and will continue with these experiences of AI in upcoming development projects”, says Magnus Viström, Innovation Manager at SCA.

Great interest in AI at ITF Automation Days

Calejo’s CEO Johannes Holmberg participated as a speaker at ITF Automation Days February 5-6 in Gothenburg.

– I notice that today there is a completely different craving from the industry after learning more about successful practical input projects in AI. Many are now tired of all the visions and beautiful words and want to know more about successful cases, he explains

This year’s ITF Automation Days at the Eriksbergshallen in Gothenburg took place on 5-6 February and gathered around 200 experts in the automation field in Sweden. The days of the year were about how digitalisation and modern automation should be implemented and how this affects the development of today’s and tomorrow’s industry.

The interest from the participants was great for AI in general, but above all for applied AI in the industry. This was mainly talked about by four companies – BillerudKorsnäs, Nouryon, ABB and Calejo Industrial Intelligence.

Peter Wallin, CEO of Piia, began by focusing on the next phase of the industry’s digitalisation in the form of AI. He said that the demand for industrial AI is increasing in line with the insights about the values ​​that technology can release.

Industries at the forefront

BillerudKorsnäs has been working focused on identifying, testing and implementing various applications of AI since 2016, and Olle Steffner, Director of IP Management, highlighted in his presentation some of the most important experiences they have made when translating words and visions into profitable and measurable results.

Stefan Malmsten, Nouryon presented a physical case, where they have built their own platform and use AI to partly optimize production efficiency and at the same time overall optimize total production based on the energy market in near real time.

Several successful projects

From Calejo, CEO Johannes Holmberg participated, who in his speech described AI’s development and potential broadly, but also came up with Calejo’s unique solution of building digital twins and optimizing processes using gray box modeling and he also presented several of the specific AI projects , which Calejo facilitates together with, among others, SCA, Boliden and Processum.

– We have now repeatedly been able to show that our patent-pending technology works and that this can be used to optimize and make major automation gains and environmental improvements in virtually all parts of the industry’s processes, he explained, adding as a summary of all meetings after two successful automation days:

– I notice that today there is a completely different craving from the industry after learning more about successful practical industrial projects in AI. Many are now tired of all the visions and beautiful words and want to know more about successful cases.

Calejo highlighted in a forest industry conference

“Through our sharp and unique technology, we have succeeded in implementing several successful AI projects in the industry. I am happy that we now in this context also can reach a wider audience by explaining the potential of AI for the forest industry, ”said Johannes Holmberg, CEO of Calejo Industrial Intelligence in connection with his recent speech at PPT (Pulp, Paper & Technology) group’s annual meeting at Sweco’s head quarter in Stockholm.

The speech was very well received by the more than one hundred people with representatives from the entire Swedish forest and process industry.

In particular, Johannes Holmberg presented the successful project that Calejo is implementing together with SCA at SCA Obbola outside Umeå.

– Here, together we have succeeded in demonstrating the optimization possibilities of energy use in the pulp process by anticipating the need for steam and using accumulated energy in the process to ensure that there is always enough steam, he explained and continued:

– We have carried out several successful projects with the process industry, all of which have confirmed that the optimization engine Calejo Optimize can be used to better understand and optimize production. We have made a successful PoC with Uniper in hydropower. In 2019 we have started several successful projects with, among others, SCA, ABB, Boliden, Optimization and Processum. We are also planning for many new projects with several of Sweden’s most AI-mature companies and we have started collaborative discussions with some of the largest and leading technology consulting companies in Sweden, all of whom are very interested in being able to collaborate around Calejo Optimize.

Other speakers during the very well-informed and informative day was Stora Enso’s Swedish director Per Lyrvall, energy guru Lars Stigsson from KIRAM, Magnus Lundmark from Domsjö Fabriker, Per Bjurbom, head of Shanying Europe, and Göran Örlander from Södra.