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An efficient, systematic, and comprehensive system for developing products with maximum consumer acceptability is presented. The three major components of the system, factor screening, optimization, and sensitivity analysis, are presented in detail. Statistical designs and data analysis procedures appropriate for each of the three components are explained and illustrated through the use of examples. How the three components interrelate is also explained, leading to a clear understanding of the integrated nature of the product optimization system. The use of consumer attribute data is an integral part of the system. Incorporating consumer attribute information provides the means for identifying why, in the eyes of the consumers, the optimum product is the “best.” Simple correlation methods for relating attribute data to overall acceptability are recommended, and the appropriate interpretation of the resulting relationships is presented. The system is based on the time-proven class of statistically designed optimization experiments called response surface methodology. This class of designed experiments includes: Plackett-Burman designs for screening ingredients or processing conditions or both for their impacts on acceptability; central composite and Box-Behnken designs, among others, for identifying the optimum product and the stability of the optimum under minor perturbations of the factor levels about the optimum conditions. Practical issues such as the total number of test products required, the number of test products a respondent can evaluate in one session, and the number of respondents required to obtain stable and reliable estimates of the acceptability rating for each test product are addressed. Practical limits, based on experience, are recommended.
consumer testing, product optimization, response surface methodology (RSM), central composite designs, Box-Behnken designs, Plackett-Burman designs
Senior research statistician, The NutraSweet Co., Research and Development, Mount Prospect, IL