A neural manufacturing a novel concept for processing modeling, monitoring and control

Conference · Sun Oct 01 00:00:00 EDT 1995

OSTI ID:135047

Law, B; Fu, C Y; Petrich, L

Semiconductor fabrication lines have become extremely costly, and achieving a good return from such a high capital investment requires efficient utilization of these expensive facilities. It is highly desirable to shorten processing development time, increase fabrication yield, enhance flexibility, improve quality, and minimize downtime. We propose that these ends can be achieved by applying recent advances in the areas of artificial neural networks, fuzzy logic, machine learning, and genetic algorithms. We use the term neural manufacturing to describe such applications. This paper describes our use of artificial neural networks to improve the monitoring and control of semiconductor process.

• Research Organization: Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
• Sponsoring Organization: USDOE, Washington, DC (United States)
• DOE Contract Number: W-7405-ENG-48
• OSTI ID: 135047
• Report Number(s): UCRL-JC-121676; CONF-951043-1; ON: DE96002573; TRN: 95:008612
• Resource Relation: Conference: International conference and exhibit of the Instrument Society of America: measurement, control, and automation, Houston, TX (United States), 22-27 Oct 1995; Other Information: PBD: Oct 1995
• Country of Publication: United States
• Language: English

Related Subjects

36 MATERIALS SCIENCE
42 ENGINEERING NOT INCLUDED IN OTHER CATEGORIES
99 MATHEMATICS
COMPUTERS
INFORMATION SCIENCE
MANAGEMENT
LAW
MISCELLANEOUS
ORGANIC SEMICONDUCTORS
FABRICATION
COMPUTER-AIDED MANUFACTURING
COMPUTERIZED CONTROL SYSTEMS
NEURAL NETWORKS