A knowledge-based approach to statistical process control

  • Authors:

  • Deborah F. Cook;Joseph G. Massey;Chuck McKinney

  • Affiliations:

  • Industrial Engineering and Forest Science Departments, Texas A&M University, College Station, TX 77843-2135, USA;Forest Science Department, Texas A&M University, College Station, TX 77843-2135, USA;Forest Science Department, Texas A&M University, College Station, TX 77843-2135, USA

  • Venue:
  • Computers and Electronics in Agriculture
  • Year:
  • 1992

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Abstract

Statistical process control (SPC) is an important tool for improving product quality and process productivity in the manufacturing environment. A manufacturing facility often applies SPC to specific manufacturing parameters, and heuristic methods of process control to various other process parameters. An expert system was developed that integrates these types of process control to monitor critical areas of the manufacturing process, detect areas of concern, and recommend action. One component of the expert system interprets SPC control charts and is in place in a particleboard mill. Another component of the system, partially complete, monitors process parameters input by operators. The final system will evaluate the results of the control chart interpretation, along with the analysis of the remaining process data, and then make recommendations for corrective action as required.