POSCO chooses SAS Predictive Asset Maintenance

SAS is implementing its Predictive Asset Maintenance solution at POSCO (Korea), one of the world’s largest steelmakers. Planned for completion by May 2009, the project is designed to improve reliability and productivity and reduce costs.

POSCO's Facility State Precision Predictive System will use SAS to optimize operations at its facilities, minimize maintenance and equipment replacement costs, and improve productivity. Efficient management, operation and maintenance of facility assets are crucial in the manufacturing industry. Using SAS, POSCO is introducing more innovative pre-detection methods, solving equipment malfunctions and predicting asset replacement. As a result, POSCO expects to improve production capacities by increasing facilities operating times and reducing unnecessary maintenance expenses. 

SAS Predictive Asset Maintenance enables POSCO to schedule necessary maintenance by detecting problems and pinpointing malfunctions and risks of failure. The innovative solution uses predictive data-mining, data integration and data management to derive an accurate and up-to-date condition report of facilities. By regularly monitoring facilities, POSCO can reduce accidents, minimize disruptions and maximize the efficiency of preventive maintenance.

"Predictive asset maintenance is an effective means for the manufacturing industry to improve performance in this era of economic crisis, which demands efficient equipment operation, productivity increase and cost reduction," Sam Cho, SAS Korea Country Manager, comments. "SAS Predictive Asset Maintenance at POSCO is designed to determine, apply and manage predictive maintenance. Its systemized methodology of process analysis and data management is based on SAS' unique data-mining techniques. Pinpointing optimum predictive maintenance means POSCO can accurately predict the point of time to perform minimum repairs at minimum expense." 

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