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A Cost Optimal Approach to Selecting a Fractional Factorial Design.

机译:选择分数因子设计的成本最优方法。

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This research develops a multistage decision process designed to obtain the maximum amount of information from the evaluation of a fractorial design while minimizing the amount of resources used in obtaining the information. The use of screening experiments in building the factorial design is investigated in order to maximize the amount of information gained. The use of sequential analysis procedures to terminate experimentation at the earliest possible time is investigated in order to minimize the amount of resources used. The research is limited to 2 to the n power factorial designs involving univariate response models assumed to come from a normal population; however, the procedure can be easily extended to any factorial design. The approach is demonstrated for an operational test involving a 2 to the 6th power factorial design and the results are compared to classical procedures. The sensitivity of the required input parameters is investigated and related applications are discussed. The proposed approach is found to be a viable method of designing, conducting, and evaluating an operational test involving a factorial experiment. (Author)

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