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Industrial AI
  • Production-centered process optimization through digital transformation
  • Enhancing productivity and efficiency based on data and embedded advanced technologies

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Analysis and Response
Case
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Diagram
Analysis and Response
Case
• Lack of manual, distributed, and real-time data management
• Partial on-site focus limits process monitoring
• Post-inspection and manual response to equipment failures
• Repetitive manual work centered on individual equipment
• Slow decision-making based on manual data
• High defect rates, inefficiencies, and slow improvement
• Improved reliability through real-time integrated data collection and analysis
• Real-time monitoring of entire process and early problem detection
• Predictive maintenance, early detection of equipment abnormalities, and automatic alarms
• Expanded automation and unmanned operation across the entire process
• Fast and accurate data-driven decision making
• Reduced defect rates and enhanced productivity and quality innovation
• Realization of automated and intelligent production processes
• Process management based on real-time data
• Quality prediction and defect reduction through AI and big data
• Strengthened advanced semiconductor production capabilities
• Reduction of unnecessary costs
• Decreased equipment downtime
• Optimization of energy and resource usage
• Embedding of 4th industrial revolution technologies such as IoT and big data
• Advancement of wafer manufacturing technologies
Diagram
Analysis and Response
Case
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