A hierarchical method for evaluating products with quantitative and sensory characteristics

References

• Beebe–Center , J. G. , Rogers , M. S. and O'Connell , D. N. ( 1955 ) Transmission of information about sucrose and saline solutions through the sense of taste. Journul of Psychology , 39 , 157 – 160 .
   Google Scholar
• Biles , W. E. ( 1975 ) A response surface method for experimental optimization of multiresponse processes. Industrial Engineering Chemistry. Process Design and Development. , 14 , 152 – 158 .
   Web of Science ®Google Scholar
• Chang , S. and Shivpuri , R. ( 1994 ) A multiple-objective decision-making approach for assessing simultaneous improvement in die life and casting quality in a die-casting process. Quality Engineering , 7 , 371 – 383 .
   Google Scholar
• Del Castillo , E. ( 1996 ) Multircsponse process optimization via constrained confidence regions. Journal of Quality Technology , 28 ( 1 ). 61 – 70 .
   Web of Science ®Google Scholar
• Del Castillo , E. , Montgomery , D. C. and McCarville , D. R. ( 1996 ) Modified desirability functions for multiple response optimization. Journal of Quality Technology , 28 ( 3 ), 337 – 345 .
   Web of Science ®Google Scholar
• Derringer , G. and Suich , R. ( 1980 ) Simultaneous optimization of several response variables. Journal of Quality Technology , 12 ( 4 ), 214 – 219 .
   Web of Science ®Google Scholar
• Elsayed , E. A. and Chen , A. ( 1993 ) Optimal levels of process parameters for products with multiple characteristics. International Journal of Production Research , 31 ( 5 ). 1117 – 1132 .
   Web of Science ®Google Scholar
• Eriksen , C. W. and Hake , H. W. ( 1955 ) Absolute judgments as a function of the stimulus range and the number of stimulus and response calcgories. Journal of Experimental Psychology , 49 , 323 – 332 .
   PubMedGoogle Scholar
• Fogliatto , F. S. ( 1997 ) The hierarchical multiresponse optimization method. Ph. D. Dissertation , Industrial and Systems Engineering Department. Rutgers University. NJ .
   Google Scholar
• Fogliatro , F. S. ( 1999 ) A hierarchical method for multiresponse experiments where some outcomes are assessed by sensory panel data. Annals of the Brazilian Conference in Industrial Engineering , Rio de Janeiro. November 1999 , on CD-ROM (in Portuguese ).
   Google Scholar
• Fogliatto , F. S. and Albin , S. L. ( 2000 ) Variance of predicted response as an optimization criterion in multi response experiments. Quality Engineering. , 12 ( 4 ), 523 – 533 .
   Google Scholar
• Fogliatto , F. S. , Albin , S. L. and Tepper , B. J. ( 1999 ) A hierarchical approach to optimizing descriptive analysis multircsponse experiments. Journal of Sensory Studies , 14 ( 4 ), 443 – 465 .
   Web of Science ®Google Scholar
• Garner , W. R. ( 1953 ) An informational analysis of absolute judgements of loudness. Journal of Experimental Psychology. , 46 , 373 – 380 .
   PubMedGoogle Scholar
• Green , P. and Carmone , F. ( 1970 ) Multidimensional Scaling and Related Techniques in Marketing Analysis. , Allyn and Bacon, Boston , MA .
   Google Scholar
• Green , P. and Wind , Y. ( 1973 ) Multiattribute Decision in Marketing, Dryden , Hinsdale , IL .
   Google Scholar
• Hake , H. W. and Garner , W. R. ( 1951 ) The effect of presenting various numbers of discrete steps on scale reading accuracy. Journal of Experimental Psychology,| 42 , 358 – 366 .
   Google Scholar
• Harrington , Jr., E. C. ( 1965 ) The desirability function. Industrial Quality Control , 21 ( 10 ), 94 – 498 .
   Google Scholar
• Jacobs , B. E. and Moskowitz , H. R. ( 1988 ) Magnitude estimation: scientific background and usc in sensory analysis, in Applied Sensory Analysis of Foods , Moskowitz . H. (ed.), CRC Press, FL .
   Google Scholar
• Kaufmann , E. L. , Lord , M. W. , Reese , T. W. and Volkmann , J. ( 1949 ) The discrimination of visual number. American Journal oj Psychology. , 62 , 498 – 525 .
   PubMed Web of Science ®Google Scholar
• Khuri , A. I. and Conlon , M. ( 1981 ) Simultaneous optimization of multiple responses represented by polynomial regression functions. Technometrics. , 23 ( 4 ), 363 – 375 .
   Web of Science ®Google Scholar
• Kim , K. and Lin , D. K. J. ( 1998 ) Dual response surface optimization: a fuzzy modeling approach. Journal of Quality Technology. , 30 ( 1 ), 1 – 10 .
   Web of Science ®Google Scholar
• Leight , R. S. and Warren , C. B. ( 1988 ) Standing panels using magnitude estimation for research and product development, in Applied Sensory Analysis of Foods , Moskowitz , H. (ed.), CRC Press, FL .
   Google Scholar
• Leon , N. A. ( 1996 ) A pragmatic approach to multi response problems using loss functions. Quality Engineering , 9 , 213 – 220 .
   Google Scholar
• Leon , R. V. , Shoemaker , A. C. and Kacker , R. N. ( 1987 ) Performance measures independent of adjustment - an explanation and extension of Taguchi's signal-to-noise ratios. Technometrics. , 29 ( 3 ), 253 – 265 .
   Web of Science ®Google Scholar
• Lewis , D. R. ( 1948 ) Psychological scales of taste. Journal of Psychology , 26 , 437 – 446 .
   PubMed Web of Science ®Google Scholar
• Lind , E. E. , Goldin , J. and Hickman , J. B. ( 1960 ) Fitting yield and cost response surfaces. Chemical Engineering Progress , 56 . 62 – 68 .
   Google Scholar
• Logothctis , N. and Haigh , A. ( 1988 ) Characterizing and optimizing multiresponse processes by the Taguchi method. Quality and Reliability Engineering International , 4 . 159 – 169 .
   Google Scholar
• Masuda , T. ( 1990 ) Hierarchical sensitivity analysis of priority used in the analytic hierarchy process. International Journal of Systems Science , 21 ( 2 ), 415 – 427 .
   Web of Science ®Google Scholar
• Moskowitz , H. R. ( 1970 ) Ratio scales of sugar sweetness. Perception and Psychology , 7 , 315 – 320 .
   Web of Science ®Google Scholar
• Moskowitz , H. R. ( 1971 ) Intensity scales for pure tastes and taste mixtures. Perception and Psychology , 9 , 51 – 56 .
   Web of Science ®Google Scholar
• Moskowitz , H. R. ( 1977 ) Magnitude estimation: notes on how. when, and why to use it. Journal of Food Quality , 3 . 95 – 227 .
   Google Scholar
• Myers , R. H. and Carter , W. H. ( 1973 ) Response surface techniques for dual response surfaces. Technontetrics , 15 , 301 – 317 .
   Web of Science ®Google Scholar
• Myers , R. H. , Khuri , A. I. and Vining , G. ( 1992 ) Response surface alternatives to the Taguchi robust parameter design approach. The American Statistician , 46 ( 2 ), 131 – 139 .
   Web of Science ®Google Scholar
• Myers , R. H. and Montgomery , D. C. ( 1995 ) Response Surface Methodology. , Wiley, New York .
   Google Scholar
• Oh , H. L. ( 1988 ) Variation tolerant design, in Proceedings of the Conference 011 Uncertainty in Engineering Design , Gaithersburg , MD , USA , pp. 137 – 146 .
   Google Scholar
• Pollack , I. ( 1952 ) Information of elementary auditory displays. Journal of the Acoustic Society of America , 24 . 745 – 749 .
   Web of Science ®Google Scholar
• Pollack , I. ( 1953 ) Information of elementary auditory displays (II). Journal of the Acoustic Society 0f America , 25 , 765 – 769 .
   Web of Science ®Google Scholar
• Pollack , I. and Ficks , L. ( 1954 ) Information of elementary multidimensional auditory displays. Journal 0f the Acoustic Society 0f America , 26 , 155 – 158 .
   Web of Science ®Google Scholar
• Pignatiello , Jr., J. J. ( 1993 ) Strategies for robust multiresponse quality engineering. IEEE Transactions , 25 , 5 – 15 .
   Web of Science ®Google Scholar
• Raiman , L. B. and Case , K. E. ( 1992 ) The development and implementation of multivariate cost of poor quality loss function. , IMSE Working Paper 92-152, Penn State University, 207 Hammond Building, University Park, PA 16802.
   Google Scholar
• Reynolds , G. S. and Stevens , S. S. (1960) Binaural summation of loudness. Journal of the Acoustic Society of America , 32, 1337–1344.
   Web of Science ®Google Scholar
• Ribeiro , J. L. and Elsayed , E. A. ( 1995 ) A case study on process optimization using the gradient loss function. International Journal of Production Research , 33 ( 12 ), 3233 – 3248 .
   Web of Science ®Google Scholar
• Saaty , T. L. ( 1977 ) A scaling method for priorities in hierarchical struct III'CS. Journal of Mathematical Psychology , 15 , 234 – 281 .
   Web of Science ®Google Scholar
• Saaty , T. L. ( 1980 ) The Analytic Hierarchy Process , McGraw-Hill, New York .
   Google Scholar
• Saaty , T. L. and Vargas , L. G. ( 1984 ) Comparison of eigenvalue, logarithmic least squares and least squares methods in estimating ratios. Mathematical Modeling , 5 , 309 – 324 .
   Web of Science ®Google Scholar
• Saaty , T. L. and Vargas , L. G. ( 1987 ) Uncertainty and rank order in the analytic hierarchy process. European Journal of Operational Research , 32 , 107 – 117 .
   Web of Science ®Google Scholar
• Stone , H. and Sidel , J. L. ( 1993 ) Sensory Evaluation Practices , Academic Press. New York
   Google Scholar
• Stone , H. , Sidcl , J. , Oliver , S. , Woolsey , A. and Singleton , R. C. ( 1974 ) Sensory evaluation by quantitative descriptive analysis. Food Technology , 28 ( 1 ), 24 – 34 .
   Google Scholar
• Triantaphyllou , E. and Mann , S. H. ( 1994 ) A computational evaluation of the original and revised analytic hierarchy process. Computers in Industrial Engineering , 26 ( 3 ), 609 – 618 .
   Web of Science ®Google Scholar
• Tribus , M. and Szonyl , G. ( 1989 ) An alternative view of the Taguchi approach. Quality Progress , 22 , 46 – 52 .
   Google Scholar
• Vargas , L. G. ( 1982 ) Reciprocal matrices with random coefficients. Mathematical Modelling , 3 , 69 – 81 .
   Web of Science ®Google Scholar
• Vining , G. G. ( 1998 ) A compromise approach to multiresponse optimization. Journal or Quality Technology , 30 ( 4 ), 309 – 313 .
   Web of Science ®Google Scholar
• Wurl , R. and Albin , S. L. ( 1999 ) A comparison of multi response optimization: sensitivity to parameter selection. Quality Engineering , 11 ( 3 ), 405 – 416 .
   Google Scholar
• Yum , B. and Ko , S. ( 1991 ) On parameter design optimization procedures. Quality and Reliability Engineering International , 7 , 39 – 46 .
   Google Scholar
• Zahedi , F. ( 1984 ) Estimation techniques and their statistical properties in the analytic hierarchy process. , Working Paper, University of Massachusetts-Amherst. MA 01003.
   Google Scholar
• Zahedi , F. ( 1986 ) The analytic hierarchy process - a survey of the method and its applications. , Interfaces, 16 ( 4 ), 96 – 108 .
   Google Scholar