“Digital Twin Will Change the Paradigm of the Power Industry”

 

OnePredict CEO Byeng Dong Youn Speaks at Digital Transformation Conference
Introducing GuardiOne… Optimizing Facility Maintenance with High Diagnosis and Prognosis Accuracy

 




It has been suggested that industrial AI-based digital twin technology will change the paradigm of the electric power industry.



On April 8^th, Professor Byeng Dong Youn<Photo>, CEO of OnePredict, delivered a speech ‘Digital Transformation, a Paradigm for Electric Power Industry’ at the Digital Transformation Conference,e of the seminars at Seoul International Electric Fair.



In his speech, Prof. Youn highlighted that industrial AI, combining domain knowledge with AI, has been well-received in the field. Especially, the digital twin market—which utilizes data collected from objects to create information and make business grow—is growing at an annual average rate of 37%, proving its potential.



Prof. Youn expected that digital twin technology will lead a paradigm change in the electric power industry. It enables optimal management of power plants based virtual data.



He also calculated that by using digital twin technology, downtime—when plant facilities are stopped—could be reduced up to 50%. In addition, utilizing prediction data based big data could reduce maintenance costs as well as increase the lifespan of facilities to up to 40%.



The cost of operation and management would also be cut down. A reduction in facility expenses would lead to an increase in financial management costs and dramatically lower the possibility of misdiagnosing the facilities.



Prof. Youn also introduced ‘GuardiOne,’ a digital twin service provided by OnePredict. GuardiOne offers solutions in 4 areas: substation facilities, turbines, wind power generation, and industrial bearings. They offer diagnosis and prognosis services based vast amounts of data from their joint projects with KEPCO as well as other power generators in the public and private sector.



GuardiOne’s diagnosis has the accuracy rate of over 95%. Its prognosis shows the accuracy rate of around 85%, dramatically reducing the possibility of misdiagnosis.





This can prevent sudden breakdowns of plant facilities and eliminate unnecessary maintenance, explained Prof. Youn.



“We can get a lot of useful data from industrial settings. The quality of data,  not the quantity, is important,” he said. “Industrial big data will help the business model grow.”







Source : ​Daewon Yun  ydw@electimes.com 

Original article : http://www.electimes.com/article.php?aid=1617858426215389002