Gwangyang Steelworks Establishes Pre-Detection System for Operational Abnormalities

Rapid Detection of Abnormal Signals During Operations

Enables Proactive Accident Prevention Measures

POSCO Gwangyang Steelworks (Director Lee Jin-su) announced that it has established an abnormal operation detection system in the No. 1 Coke Plant, enabling faster and more accurate detection of abnormal signals that may occur during operations, thereby enhancing safety.

The abnormal operation monitoring system allows workers to identify problems in a timely manner and, if necessary, take measures to stop equipment operation.

The photo shows equipment operating at the No. 1 Coke Plant of Gwangyang Steelworks.

This system establishment was carried out as part of the Smart Predictive Maintenance technology advancement strategy that Gwangyang Steelworks is promoting to accelerate the factory's smart factory transformation and strengthen worker safety.

Gwangyang Steelworks is digitalizing and automating equipment inspections to improve worker safety and inspection accuracy, integrating data scattered across equipment, developing predictive technologies to assess equipment conditions, and operating systems that apply predictive technologies to equipment to detect abnormal signs in advance.

The abnormal operation detection system implemented at the No. 1 Coke Plant aims to proactively detect signs of safety accidents such as increased pipe pressure or waste gas leaks, thereby reducing the possibility of accidents.

For example, if the pressure inside the equipment piping shows signs of rising above the standard level, the detection system immediately identifies this and quickly sends an alert to PIMS (POSCO Intelligent Management System).

PIMS is a POSCO-type Smart Predictive Maintenance system that assists diagnosis and life expectancy prediction based on past equipment operation history and operational data. Operators managing PIMS can recognize abnormal signals in a timely manner through these alerts.

By promptly transmitting abnormal signals like this, workers can take preemptive measures such as stopping equipment operation, enabling rapid preventive actions to avoid safety accidents, which is expected to significantly reduce the likelihood of accidents.

Lee Jin-su, Director of Gwangyang Steelworks, said, “We expect that the system developed this time will further enhance the predictive maintenance technology at Gwangyang Steelworks,” and added, “We will continue to lead the establishment of a safe smart factory by applying advanced Smart Predictive Maintenance technologies across the entire steelworks process.”

Meanwhile, Gwangyang Steelworks is accelerating its smart factory transformation strategy to improve safety by operating predictive maintenance technologies across various processes, including establishing a system that predicts the wear amount of parts in rolling mill equipment to proactively determine replacement timing.

This content was produced with the assistance of AI translation services.