Diagnostic Quality Problem Solving: A Conceptual Framework and Six Strategies

References

• Anderson-Cook, C.M., L. Lu, G. Clark, S. P. DeHart, R. Hoerl, B. Jones, R. J. MacKay, D. C. Montgomery, P. A. Parker, J. Simpson, R. Snee, S. Steiner, J. Van Mullekom, G. G. Vining, and A. G. Wilson. 2012. Statistical engineering — Forming the foundations. Quality Engineering 24: 110–132.
   Web of Science ®Google Scholar
• Balakrishnan, A., R. Kalakota, P. Siow, and A. B. Whinston. 1995. Document-centered information systems to support reactive problem-solving in manufacturing. International Journal of Production Economics 38: 31–58.
   Google Scholar
• Bhote, K. R. 1991. World class quality. New York: Amacom.
   Google Scholar
• Boreham, N. C. 1986. A model of efficiency in diagnostic problem solving: Implications for the education of diagnosticians. Instructional Science 15: 191–211.
   Web of Science ®Google Scholar
• Breyfogle, F. W. 2003. Implementing Six Sigma: Smarter solutions using statistical methods, second edition. New York: Wiley.
   Google Scholar
• Chakravorty, S. S. 2009. Six Sigma programs: An implementation model. International Journal of Production Economics 119: 1–16.
   Web of Science ®Google Scholar
• Chittaro, L., and R. Ranon. 2004. Hierarchical model-based diagnosis based on structural abstraction. Artificial Intelligence 155: 147–182.
   Google Scholar
• Clancey, W. J. 1988. Acquiring, representing and evaluating a competence model of diagnostic strategy. In The Nature of Expertise, eds. M. Chi, R. Glaser, and M. Farr, 343–419. London: Lawrence Erlbaum Associates.
   Google Scholar
• Custers, E. J. F. M., G. Regehr, and G. R. Norman. 1996. Mental representations of medical diagnostic knowledge. Academic Medicine 71: s55–s61.
   PubMed Web of Science ®Google Scholar
• Dasgupta, T., N. Adiga, and C. F. J. Wu. 2011. Another look at Dorian shainin's variable search technique. Journal of Quality Technology 43: 273–287.
   Web of Science ®Google Scholar
• Davis, R., and W. C. Hamscher. 1988. Model-based reasoning: Troubleshooting. In Exploring Artificial Intelligence, edited by H. E. Shrobe, 297–346. San Francisco: Morgan Kaufmann.
   Google Scholar
• De Mast, J. 2011. The tactical use of constraints and structure in diagnostic problem solving. Omega 39: 702–709.
   Google Scholar
• De Mast, J., and J. Lokkerbol. 2012. An analysis of the Six Sigma DMAIC method from the perspective of problem solving. International Journal of Production Economics 139: 604–614.
   Web of Science ®Google Scholar
• De Mast, J., K. C. B. Roes, and R. J. M. M. Does. 2001. The multi-vari chart: A systematic approach. Quality Engineering 13: 437–447.
   Google Scholar
• De Mast, J. and A. Trip. 2007. Exploratory data analysis in quality improvement projects. Journal of Quality Technology 39: 301–311.
   Web of Science ®Google Scholar
• Elstein, A. S., and A. Schwarz. 2002. Clinical problem solving and diagnostic decision making: Selective review of the cognitive literature. British Medical Journal 324: 729–732.
   PubMed Web of Science ®Google Scholar
• Eva, K. W. 2005. What every teacher needs to know about clinical reasoning. Medical Education 39: 98–106.
   PubMed Web of Science ®Google Scholar
• García-Muñoz, S., T. Kourti, J. F. MacGregor, A. G. Mateos, and G. Murphy. 2003. Troubleshooting of an industrial batch process using multivariate methods. Industrial Engineering and Chemistry Research 42: 3592–3601.
   Web of Science ®Google Scholar
• George, M. L., D. T. Rowlands, M. Price, and J. Maxey. 2004. The Lean Six Sigma pocket toolbook: A quick reference guide to 100 tools for improving quality and speed. New York: McGraw-Hill.
   Google Scholar
• Gitlow, H. S., and D. M. Levine. 2004. Six Sigma for green belts and champions: Foundations, DMAIC, tools, cases, and certification. New Jersey: FT Press.
   Google Scholar
• Gryna, F. M. 1988. Quality improvement. In Juran's Quality Handbook, 4th edition, ed. J. M. Juran, 22.1–74. New York: McGraw-Hill.
   Google Scholar
• Ho, J. K. K., and D. Sculli. 1997. The scientific approach to problem solving and decision support systems. International Journal of Production Economics 48: 249–257.
   Google Scholar
• Hopp, W. J., and M. K. Spearman. 2008. Factory physics, third edition. New York: McGraw-Hill.
   Google Scholar
• Juran, J. M. 1998. The quality improvement process. In Juran's Quality Handbook, fifth edition, eds. J. M. Juran, and A. B. Godfrey, 5.1–74. New York: McGraw-Hill.
   Google Scholar
• Kassirer, J. P., and A. Gorry. 1978. Clinical problem solving: A behavioral analysis. Annals of Internal Medicine 89: 245–255.
   PubMed Web of Science ®Google Scholar
• Kepner, C. H., and B. B. Tregoe. 1997. The new rational manager. Princeton: Kepner-Tregoe.
   Google Scholar
• Keravnou, E. T., and L. Johnson. 1989. Towards a generalized model of diagnostic behaviour. Knowledge-based Systems 2: 165–177.
   Google Scholar
• Keravnou, E. T., and J. Washbrook. 1989. Deep and shallow models in medical expert systems. Artificial Intelligence in Medicine 1: 11–28.
   Google Scholar
• Kolodner, J. L., R. L. Simpson, and E. Sycara. 1985. A process model of case-based reasoning in problem solving. In Proceedings of the Ninth International Joint Conference on Artificial Intelligence, 284–290. Los Altos, CA: Kaufmann.
   Google Scholar
• Lucas, P. J. F. 1997. Model-based diagnosis in medicine. Artificial Intelligence in Medicine 10: 201–208.
   PubMed Web of Science ®Google Scholar
• MacDuffie, J. P. 1997. The road to ‘Root Cause’: Shop-floor problem-solving at three auto assembly plants. Management Science 43: 479–502.
   Web of Science ®Google Scholar
• Milne, R. 1987. Strategies for diagnosis. IEEE Transactions On Systems, Man, and Cybernetics 17: 333–339.
   Web of Science ®Google Scholar
• Mooren, J., J. De Mast, and R. J. M. M. Does. 2012. Quality quandaries: The case of premature drill wear-out. Quality Engineering 24: 354–359.
   Web of Science ®Google Scholar
• Morris, N. M., and W. B. Rouse. 1985. Review and evaluation of empirical research in troubleshooting. Human Factors 27: 503–530.
   Web of Science ®Google Scholar
• Mozetič, I. 1991. Hierarchical model-based diagnosis. International Journal of Man-Machine Studies 35: 329–362.
   Google Scholar
• Newell, A., and H. A. Simon. 1972. Human problem solving. Englewood Cliffs, NJ: Prentice-Hall.
   Google Scholar
• Niiniluoto, I. 1999. Defending abduction. Philosophy of Science 66: S436–S451.
   Web of Science ®Google Scholar
• Norman, G. R. 2005. Research in clinical reasoning: Past history and current trends. Medical Education 39: 418–427.
   PubMed Web of Science ®Google Scholar
• Norman, G. R., L. R. Brooks, C. L. Colle, and R. M. Hatala. 2000. The benefit of diagnostic hypotheses in clinical reasoning: Experimental study of an instructional intervention for forward and backward reasoning. Cognition and Instruction 17: 433–448.
   Web of Science ®Google Scholar
• Pople, H. E. 1982. Heuristic methods for imposing structure on ill-structured problems: The structuring of medical diagnosis. In Artificial Intelligence in Medicine, ed. P. Szolovits, 119–190. Boulder, CO: Westview Press.
   Google Scholar
• Portinale, L., P. Torasso, C. Ortalda, and A. Giardino. 1994. Using case-based reasoning to focus model-based diagnostic problem solving. In Lecture Notes in Computer Science, vol. 837: Topics in Case-Based Reasoning, eds. S. Wess, K. D. Althoff, M. M. Richter, 325–337. Berlin: Springer.
   Google Scholar
• Pyzdek, T. 2003. The Six Sigma handbook: The complete guide for greenbelts, blackbelts, and managers at all levels, 2nd edition. New York: McGraw-Hill.
   Google Scholar
• Rasmussen, J. 1981. Models of mental strategies in process plant diagnosis. In Human detection and diagnosis of system failures, eds. J. Rasmussen and W. B. Rouse, 241–258. New York: Plenum Press.
   Google Scholar
• Rouse, W. B. 1983. Models of human problem solving: Detection, diagnosis, and compensation for system failures. Automatica 19: 613–625.
   Web of Science ®Google Scholar
• Schaafstal, A., J. M. Schraagen, and M. van Berlo. 2000. Cognitive task analysis and innovation of training: The case of structured troubleshooting. Human Factors 42: 75–86.
   PubMed Web of Science ®Google Scholar
• Shainin, R. 1993. Strategies for technical problem solving. Quality Engineering 5: 433–448.
   Google Scholar
• Smith, G. F. 1988. Towards a heuristic theory of problem structuring. Management Science 34: 1489–1506.
   Web of Science ®Google Scholar
• Smith, G. F. 1998. Determining the cause of quality problems: Lessons from diagnostic disciplines. Quality Management Journal 5: 24–41.
   Google Scholar
• Smith, P. J., W. C. Giffin, T. H. Rockwell, and M. Thomas. 1986. Modeling fault diagnosis as the activation and use of a frame system. Human Factors 28: 703–716.
   Web of Science ®Google Scholar
• Steiner, S. H., and R. J. MacKay. 2005. Statistical engineering. Milwaukee: ASQ Quality Press.
   Google Scholar
• Steiner, S. H., and R. J. MacKay. 2013. Statistical engineering and variation reduction. Quality Engineering, in press.
   Google Scholar
• Steiner, S. H., R. J. MacKay, and J. S. Ramberg. 2008. An overview of the Shainin System for quality improvement. Quality Engineering 20: 6–19.
   Google Scholar
• Torasso, P., and G. Torta. 2005. Compact diagnoses representation in diagnostic problem solving. Computational Intelligence 21: 27–68.
   Google Scholar
• Venkatasubramanian, V., R. Rengaswamy, S. N. Kavuri, and K. Yin. 2003a. A review of process fault detection and diagnosis, Part I: Quantitative model-based methods. Computers # Chemical Engineering 27: 293–311.
   Web of Science ®Google Scholar
• Venkatasubramanian, V., R. Rengaswamy, and S. N. Kavuri. 2003b. A review of process fault detection and diagnosis, Part II: Qualitative models and search strategies. Computers # Chemical Engineering 27: 313–326.
   Web of Science ®Google Scholar
• Wagner, C. 1993. Problem solving and diagnosis. Omega 21: 645–656.
   Web of Science ®Google Scholar