How data can help industry combat a major source of global warming
Digitalization of industry is a huge opportunity to accelerate transformation in our energy systems, stabilize our climate and help economies adapt.
Monitoring by the World Meteorological Organization has tracked record growth in the concentration of carbon dioxide in our atmosphere, reaching 403.3 parts per million – up 145 percent on pre-industrial levels. The last time Earth experienced a comparable concentration of CO2 was 3-5 million years ago when temperatures were 2-3°C warmer and sea level was 10-20 meters higher than today.
The long-term targets set by policy makers call for energy-intensive buildings and industries to cut emissions by 80-90 percent by 2050. This will only be possible if we take action early: the longer we delay, the more drastic and costly the solutions will become.
The reason I joined ABB from Microsoft is because I see the next wave of data-driven innovation will be in energy. The only way forward is for energy consumption and production at industrial sites to become smarter. Utilities will naturally play a role, but factories and commercial buildings have both the motivation and the means to do things that other stakeholders simply cannot.
The technology and the IT infrastructures needed to digitize power are already available and online – it has been more than a year since the commercial launch of ABB AbilityTM , the company’s industry-leading portfolio of digital solutions, and more than five years since our first smart circuit breaker, the Emax 2, came out. A major shift in the way industry thinks is also underway. I believe 2018 will go down as the year that digitalization established itself as a guiding force on factory floors.
Data-driven used to mean spreadsheets shaping management decision making. But this has evolved with digitalization – data-logging and analysis is automated, leaving management with more time to focus on execution. Applying this same strategy to energy management is just common sense as energy costs often account for 3-6 percent of total costs in most sectors. (http://www.wiod.org/home)
Progress requires two things: domain experts and data. Companies such as ABB must aggregate data to build datasets needed for machine learning and apply their expertise to work, ensuring every artificial intelligence service delivers real value and reliability.
The first step is about understanding the hardware and its performance better. It means predictive maintenance can replace unnecessary routine maintenance. And, once our AI understands what the machines look like when they function efficiently, it can instantly spot when something goes wrong.
Around 12 percent of the energy used in factories is for either heating or cooling the building. Our aim is for AI to spot a malfunctioning unit immediately, not a month later when the excess power consumption is spotted in a routine report.
Similar technology can also be applied to power supply issues on the fast-growing number of factories using renewables on site. By collecting environmental data like temperature, humidity and vibration, we can create more complex models that can correlate historical environmental and operational measurements.
If we can address the energy spent on the temperature inside the factory, we will take another small, but valuable step towards stabilizing our Earth’s climate. AI will be able to forecast demand and the likely yield from solar or wind energy plants, so that sites can store enough energy either from the renewables or from the grid during off-peak times.
There are some who doubt that human activity is responsible for climate change, but no one can deny that energy is expensive and managing the way we consume and produce power could be a lot smarter.
That’s why we are looking for customers to work with us on advances to these technologies. For us, size doesn’t matter, it’s more a question of speed. ABB is committed to making real progress on this front and we welcome other fast companies as partners. Together, we can make sure digitalization makes a difference.
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