Abstract :
The use of AI methods to monitor and control semiconductor fabrication in a state-of-the-art manufacturing environment called the Rapid Thermal Multiprocessor is described. Semiconductor fabrication involves many complex processing steps with limited opportunities to measure process and product properties. By applying additional process and product knowledge to that limited data, AI methods augment classical control methods by detecting abnormalities and trends, predicting failures, diagnosing, planning corrective action sequences, explaining diagnoses or predictions, and reacting to anomalous conditions that classical control systems typically would not correct. Research methodology and issues are discussed, and two diagnosis scenarios are examined.<>
Keywords :
computerised monitoring; knowledge based systems; manufacturing computer control; semiconductor device manufacture; AI methods; Rapid Thermal Multiprocessor; abnormalities; anomalous conditions; corrective action sequences; explaining diagnoses; intelligent control; monitoring; predicting failures; process knowledge; product knowledge; semiconductor fabrication; semiconductor manufacturing equipment; trends; Artificial intelligence; CMOS process; Circuit testing; Conducting materials; Intelligent control; Manufacturing processes; Monitoring; Semiconductor device manufacture; Silicon; Temperature;