‘Equipment Malfunction, Complete Prevention’ … Pohang Steelworks, Deputy Manager Lee Kyung-jun Wins ‘Best Award’ at Predictive Maintenance Technology Competition

Smart Prevention of Safety, Production, and Quality Accidents

Assistant Manager Lee Kyung-jun of the Steelmaking Equipment Department at Pohang Steelworks is presenting the results of predictive maintenance technology development.

[Asia Economy Yeongnam Reporting Headquarters Reporter Yeo Jong-gu] POSCO Pohang Steelworks held a Predictive Maintenance (PIMS) Technology Competition on the 25th at the Equipment Technology Center auditorium.

Predictive maintenance technology uses big data collected from equipment sensors or process control to monitor equipment status and predict failures.

By applying this technology, equipment abnormalities can be detected in advance and maintenance can be performed proactively, preventing equipment accidents.

In particular, the greatest strength of predictive maintenance technology is that it prevents safety, production, and quality accidents through efficient equipment management and improves the convenience of maintenance workers' tasks.

The Equipment Division of Pohang Steelworks organized the competition to share cases of predictive maintenance technology development that contributed to preventing production and quality disruptions, aiming to increase the use of on-site predictive maintenance technology.

On the day of the competition, eight projects from different departments passed the preliminary round.

The judges comprehensively evaluated ▲collaboration and improvement level ▲effectiveness ▲spreadability to select one grand prize and three excellence awards.

The grand prize was awarded to Deputy Manager Lee Kyung-jun of the Steelmaking Equipment Department, who presented a case of developing a wireless charging management system by linking the Internet of Things and predictive maintenance technology. This case was highly evaluated not only for significantly reducing equipment failures but also for enhancing safety by reducing manual equipment inspections.

In addition, Deputy Manager Lee Hyung-gu and Staff Member Lim Sung-hoon of the Ironmaking Equipment Department, Deputy Manager Oh Seung-wook of the Rolling Equipment Department, and Deputy Manager Yang Jong-hoon of the EIC Technology Department developed abnormality prediction technology models and received excellence awards.

Bang Seok-ju, Deputy Director of Pohang Steelworks, said, “I hope this will be a good opportunity to shift to an advanced maintenance method based on prediction,” and added, “While technology development is important, I hope we also reflect on how well the system is being utilized and continue to raise the level of equipment abnormality prediction technology.”

Pohang Steelworks plans to continuously hold predictive maintenance technology competitions to advance predictive maintenance technology and expand it throughout all plants.

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