Digital Transformation of the Graphitization Furnace Industry: From Exp"&"erience-Driven to Data-Driven
Traditional graphitization production heavily relies on the experience of master craftsmen—when to heat up, when to hold, and when to cool down—all based on intuition. This approach has two fatal flaws: first, the ex"&"perience is lost when the master craftsmen retire; second, human intuition is prone to error, resulting in poor batch-to-batch consistency.
Digital transformation is changing all of this.
Data Acquisition: Ful"&"l-Process Coverage
Deploying a comprehensive sensor network on the graphitization furnace:
- Temperature: Real-time monitoring of temperature at multiple points
- Pressure: Furnace pressure, g"&"as pressure
- Flow Rate: Gas flow rate for each path
- Power: Power output power
- Atmosphere: Gas composition, dew point, oxygen content
All data is sampled at the"&" second level and automatically stored to form a complete data asset.
Data Analysis: From Data to Insight
Through a data analysis platform, achieve the following:
- Process Optimization: Analyze historical best processes to find the optimal parameter combination
- Quality Prediction: Predict product quality based on real-time data and adjust in advance
- Anomaly Detection: Automati"&"cally identify anomalies that deviate from the normal pattern
- Root Cause Analysis: Quickly locate the cause after a quality problem occurs
Digital Twin: Virtual Optimization of Reality
Value: Typical results of implementing digital transformation include: a 5-10% increase in yield, a 1"&"0-15% reduction in energy consumption, and a 30% shortening of process development cycles. Digital transformation is not just about spending money; it's a strategic initiative with a high return on investment. With the advent of the AI era and the suppo"&"rt of AI intelligent agents, this iterative speed will advance even more rapidly.
