A semiconductor chip enterprise relied on manual spot checks at stations for film thickness, making it difficult to analyze film thickness anomalies in the same or different batches; massive data on the equipment side was unused; lacked effective means for CMP process film thickness and defect anomaly analysis, with high product defect rates.

GETECH helped achieve CMP&TF process quality optimization and improvement through an integrated solution. Imported all equipment and process-related parameters, used various automated feature mining algorithms like dimensionality reduction and expansion to continuously screen and extract, creating a user-modifiable factor set for training; established CMP film thickness anomaly and defect root cause analysis models; used virtual measurement to build models with complex algorithms to predict film thickness values with high accuracy, intercept anomalies in real-time, achieving 'real-time full inspection' of feature values, reducing station spot check frequency by 60%. The solution reduced the product defect rate supported by CMP by 70%, generating annual economic benefits of about 10 million yuan.