Episode 17: How AI can improve the predictive power of tribology, the tribological challenges of electrical vehicles and why the energy transition should be an evolution
Dr. Boris Zhmud, born in Russia, now based in Stockholm, Sweden, has more than 20 years of professional experience in lubricants and lubrication engineering. He has authored or co-authored more than 80 peer-reviewed publications and has several patents. He currently consults on tribological problems for companies in Europe, including in Germany and in the UK. He is also a member of the British Royal Society of Chemistry (RSC), the Society of Automotive Engineers (SAE), and the Society of Tribologists and Lubrication Engineers (STLE).
In tribology, theory is good to explain observations in retrospect. But the predictive power of tribology is rather limited, he says. “Tribology is very much an empirical science. In empirical science, you have a huge amount of data, but what is usually published is only positive results.” However, he believes that negative results are as valuable as positive results.
“That’s really what can be done by using big data analysis and artificial intelligence (AI). You can accumulate all your previous test information. You can get much more reliable information for your next step.”
Artificial intelligence is a very important area for the development of tribology, he says. “It is really remarkable what you can achieve.”
In this episode of F+L Webcast, Dr. Zhmud discusses the beauty of tribology, the new tribological challenges of electrical vehicles, and why the energy transition should be an evolution, not a revolution.