Interpreting statistical process control (SPC) charts using machine learning and expert system techniques
Conference Paper · June 1992
Abstract
Statistical process control (SPC) charts are one of several tools
used in quality control. The SPC quality control tool has been
under-utilized due to the lack of experienced personnel able to identify
and interpret patterns within the control charts. The Special Projects
Office of the Center for Supportability and Technology Insertion (CSTI)
has developed a hybrid machine-learning and expert-system software tool
which automates the process of constructing and interpreting control
charts. The software tool draws control charts, identifies various chart
patterns, advises what each pattern means, and suggests possible
corrective actions. The application is easily modifiable for process
specific applications through simple modifications to the knowledge base
portion using any word processing software. The authors discuss control
charts, software functionality, software design, machine learning, and
the expert system
used in quality control. The SPC quality control tool has been
under-utilized due to the lack of experienced personnel able to identify
and interpret patterns within the control charts. The Special Projects
Office of the Center for Supportability and Technology Insertion (CSTI)
has developed a hybrid machine-learning and expert-system software tool
which automates the process of constructing and interpreting control
charts. The software tool draws control charts, identifies various chart
patterns, advises what each pattern means, and suggests possible
corrective actions. The application is easily modifiable for process
specific applications through simple modifications to the knowledge base
portion using any word processing software. The authors discuss control
charts, software functionality, software design, machine learning, and
the expert system
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