Artificial intelligence (AI) serves (or will end up serving) for everything. Among the areas where the industry is used. There he works to improve efficiency and achieve energy savings, precisely in a sector that requires this type of monitoring solutions for its great consumption.
The study ‘Energia by Smarkia: expectations, penetration and contribution of artificial intelligence in energy management in large companies’, prepared by the GFK consultant, reveals that only 9% of companies use AI for the optimization of consumption and the improvement of their energy efficiency. Of this handful of companies, 98% show their satisfaction.
Although the ignorance of the AI potential in energy management seems installed in the industry, the study indicates that 75% believe interesting to hire some solution of this type. By subsectors, the companies of the productive and manufacturing industry (61%) are, together with those of the tourism sector (70%) and those of the food industry, the great consumption and the retail (61%), those that exhibit the greatest knowledge of the possibilities of AI.
Research reviews the ‘contribution’ of the energy crisis in the decision of the companies to seek measures that limit energy consumption, with a double purpose: reduce costs and limit the environmental impact.
Monitoring
The use of AI to achieve energy efficiency and cost reduction is a pending subject of the industry, but Jorge Pereira, director of industry and great consumption of Softtek, clarifies this statement: «In general it can be agreed that it is so, but not in large companies, where the cost of energy consumption can become 30% of production, even more so in the steel, where it reaches half. That is why they have been with AI solutions for a while to reduce spending. Then there are a lot of industries, small or medium or that do not know technology very well or that they calculate that it will not be interesting savings. Some companies are waiting for a Microsoft of the energy AI, to implant it for little money and start it ».
Softtek is a company based in Madrid that implements technological solutions in the industry to reduce energy consumption thanks to AI. “We offer monitoring and optimization resources,” he explains. Some are energy optimization specifically, for example, of industrial equipment or generation equipment, and others, applications of optimization algorithms for a specific industrial process ».
The quantification of savings depends on the subsector and even the characteristics of each particular installation, even if it is from the same company, says Pereira: «Although the normal thing is a percentage between 10 and 15%, which is already a lot. But the time reduction of some processes is also achieved ».
Predictive model
Another company that provides solutions to achieve energy efficiency in the industry through AI is Smarkia, based in León and whose shareholding is part of Repsol. Dairy, food, chemical, pharmaceutical companies benefit from their proposals.
Nuria del Río, its support director, states that “they use AI since the beginning of the process to improve the quality of the data and detect anomalies and deviations.” «We also use it for the efficient use of resources, because industries are the great consumers. Algorithmia and patterns make savings possible without even having to make changes in hardware. We have sometimes reached 30%although companies with machinery from the seventies do not have the same possibilities, ”he says.
The predictive model acts as a guide for decision -making, details Smarkia support director: “You can make forecasts and calculations that help the client to be put in the short or medium term future and get ahead of future problems and avoid production stops, which generate important money losses.” One of the company’s tools is Flexia, a system based on AI that automates the entire energy cycle, from the optimization of consumption to participation in energy markets.
The processes that AI differ in terms of the subsector or the factory in particular, clarifies Nuria del Río: «There are companies that require a lot of heat, other steam, other cold, to which they impact external temperatures and require isolation. The AI allows you to not have to be categorizing each process one by one, but that she will learn.
The impact on the sustainability of cost savings is always positive. The efficient use of resources reduces the carbon footprint, a measurement that also makes smarkia for its customers. «The industry, right now, has the focus on sustainability. Any improvement that is made, it shows, ”he says.
Bigda Solutions was born as a kind of spin-off in 2016 of Orbea Meteo for Energy, a company founded in 2013 by Ibon Salbidegoitia and Amaia Acha-Forea in Álava, which made meteorological predictive models in the generation of renewable energy. Bigda Solutions proposes AI -based solutions for car manufacturing companies, such as Mercedes Benz (energy consumption management) or Volkswagen (boilers and air conditioning); Siderúrgica Sidenor; or chemistry Bilbao of tar. Amaia Acha-Forea, co-founder of Bigda Solutions and head of Development and Business, compares the examination of the previous situation of each company with blood tests: «How much can you save? There are companies that do not know their consumption. You have to put counters, start analyzing to know what the problems are and diagnose what improved you can have in each process ».
Planned savings
He estimates that “a saving between 5 and 20%is feasible.” “Our generation of predictive models – he says – takes into account the past consumption, how they have behaved in different circumstances, in order to Optimize processes and see what improvements there can. And in the future, alarms are created for real time depending on the parameters to detect consumption deviations ».
The variables that must be considered differ in each industrial process, comments: “The ambient temperature, the relative humidity, the consumption of the raw material when introducing it into a machine … the client informs us of the parameters that can influence.”
The AI model for the energy efficiency of each installation is configured for each company, says Acha-Forea: «We have mounted a system that we help to start, but then the employees of that industry can develop, without any knowledge of code, predictive models. What we want is to give power to the technicians themselves and that according to different parameters prove how it affects energy consumption ».
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