Statistical quality control (SQC) is an effective tool that ensures quality products and services by means of control charts, the essence of SQC, and sampling plans. While the computation of sample statistics and the development of control charts are routine exercises, the interpretation of chart patterns, trends and the associated diagnosis of assignable causes requires expert knowledge. The present trend is to develop a quality control system and apply it throughout the company (company-wide quality control CWQC or total quality control - TQC). This frequently means involvement of non-quality personnel in QC teams. Additionally, many companies are faced with a shortage of experienced quality controllers and individuals who can train and educate others on statistical quality control techniques. Quality control expert systems (QCESs) are considered as one way to alleviate these difficulties. In recent years, quality control expert systems have attracted the attention of both quality researchers and practitioners. This paper reviews existing quality control expert systems and recommends a set of quality engineering techniques that should be used to form a knowledge base, the heart of an expert system.
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Alexander, S. M. and Jagannathan, V. (1986) Advisory system for control chart selection. Computers and Industrial Engineering, 10(3), 171–177.
ANSI/ASQC (1985) American National Standards Z1.1, Z1.2, Z1.3.
Banks, J. (1989) Principles of Quality Control, John Wiley & Sons, New York.
Barr, A. and Feigenbaum, E. (1981) The Handbook of Artificial Intelligence, Vol. 1, William Kaufmann, CA.
Braun, R. J. (1990) Turning computers into experts. Quality Progress, Feb., 71–75.
Brillhart, D. C. and Wible, S. F. (1989) An expert system for real-time process characterization and control, in IEEE/ CHMT IEMT Symposium, pp. 76–83.
Champ, C. W. and Woodall, W. H. (1987) Exact results for Shewhart control charts with supplementary runs rules. Technometrics, 29(4), 393–399.
Dagli, C. and Stacey, R. (1988) A prototype expert system for selecting control charts. International Journal of Production Research, 26(5), 987–996.
Duncan, A. J. (1956) The economic design of ¯x charts used to maintain current control of a process. Journal of American Statistical Association, 51, 228–242.
Evans, J. R. and Lindsay, W. M. (1988) A framework for expert system development in statistical quality control. Computers and Industrial Engineering, 14(3), 335–343.
Frerichs, D. K. (1990) Integrating a diagnostic expert system with statistical process control in a modern distributed control system. ISA, 1981–1987.
Gipe, J. P. and Jasinski, N. D. (1986) Expert system applications in quality assurance. ASQC Quality Congress Transactions, 40, 280–284.
Hosni, Y. A. and Elshennawy, A. K. (1988) Quality control and inspection: knowledge-based quality control system. Computers and Industrial Engineering, 15(1–4), 331–337.
Kuo, T. Y. (1989) Control charts interpretation system - a prototype expert system for patterns recognition on control charts, Master's Thesis, Ohio University, Athens, OH.
Love, P. L. and Simaan, M. (1988) Automatic recognition of primitive changes in manufacturing process signals. Pattern recognition, 21(4), 333–342.
Love, P. L. and Simaan, M. (1989) A knowledge-based system for the detection and diagnosis of out-of-control events in manufacturing processes, in Proceedings of 1989 American Control Conference Vol. 3, Published by IEEE, pp. 2394–2399.
MacKertich, N. A. (1990) Precontrol vs. control charting: a critical comparison. Quality Engineering, 2(3), 253–260.
Montgomery, D. C. (1985) Introduction to Statistical Quality Control, John Wiley & Sons, New York.
Nelson, L. S. (1984) The Shewhart control chart - tests for special causes. Journal of Quality Technology, 16(4), 237–239.
Nelson, L. S. (1985) Interpreting Shewhart X-BAR control charts. Journal of Quality Technology, 17(2), 114–116.
Ott, E. R. (1975) Process Quality Control: Troubleshooting and Interpretation of Data, McGraw-Hill, New York.
Pandelidis, I. O. and Kao, J. F. (1990) DETECTOR: a knowledge-based system for injection modeling diagnostics. Journal of Intelligent Manufacturing, 1(1), 49–58.
Pandit, S. M. and Wu, S. M. (1983) Time Series and System Analysis, with Applications, John Wiley & Sons, New York.
Rowan, D. A. (1989) On-line expert systems in process industries. AI Expert, Aug., 30–38.
Scott, L. L. and Elgomayel, J. I. (1987) Development of a rule based system for statistical process control chart interpretation. American Society of Mechanical Engineers, Production Engineering Division (PED), 27, 73–91.
Wadsworth, H. M., Stephens, K. S. and Godfrey, A. B. (1986) Modern Methods for Quality Control and Improvement, John Wiley & Sons, New York.
Western Electric (1956) Statistical Quality Control Handbook, AT&T, Princeton, New Jersey.
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Kuo, T., Mital, A. Quality control expert systems: a review of pertinent literature. J Intell Manuf 4, 245–257 (1993). https://doi.org/10.1007/BF00124138
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DOI: https://doi.org/10.1007/BF00124138