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One of the main goals of process engineering in the semiconductor industry is to improve wafer fabrication productivity
and throughput. Engineers must work continuously toward this goal in addition to performing sustaining
and development tasks. To accomplish these objectives, managers must make efficient use of engineering resources.
One of the tools being used to improve efficiency is the diagnostic expert system. Expert systems are knowledge
based computer programs designed to lead the user through the analysis and solution of a problem.
Several photolithography diagnostic expert systems have been implemented at the Hughes Technology Center to
provide a systematic approach to process problem solving. This systematic approach was achieved by documenting
cause and effect analyses for a wide variety of processing problems. This knowledge was organized in the form of
IF-THEN rules, a common structure for knowledge representation in expert system technology. These rules form the
knowledge base of the expert system which is stored in the computer. The systems also include the problem solving
methodology used by the expert when addressing a problem in his area of expertise. Operators now use the expert
systems to solve many process problems without engineering assistance. The systems also facilitate the collection of
appropriate data to assist engineering in solving unanticipated problems.
Currently, several expert systems have been implemented to cover all aspects of the photolithography process.
The systems, which have been in use for over a year, include wafer surface preparation (HMDS), photoresist coat and
softbake, align and expose on a wafer stepper, and develop inspection. These systems are part of a plan to implement
an expert system diagnostic environment throughout the wafer fabrication facility.
In this paper, the systems' construction is described, including knowledge acquisition, rule construction,
knowledge refinement, testing, and evaluation. The roles played by the process engineering expert and the knowledge
engineer are discussed. The features of the systems are shown, particularly the interactive quality of the consultations
and the ease of system use.
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