Capacity planning considerations in the context of design



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The purpose of this research was twofold. The first objective was to contribute to the ability of planning and implementing a capacity strategy. The second objective was to develop and test an algorithmic process based on sampling theory which would enable an analyst to explore statistically the response surface of an objective function. Specifically, he would be able to infer the optimum value of any objective function and to compare this optimum value to the best value encountered during the sampling process. The approach used for this research was to present and illustrate a design morphology previously described in the literature and use this formal structure as a vehicle for developing the capacity planning theme. Two phases of capacity planning were identified and a nonlinear mathematical model was synthesized that integrated the design parameters considered in the first phase. After developing the mathematical model, arguments were made that formal optimization was not yet required and of more immediate interest to the analyst was an evaluation of the response surface of the objective function. A sampling theory based algorithm, which provides this very capability, was presented and later tested using the data of the paint factory (Holt, Modigliani and Simon, 1955). The results were significant and confirmed the usefulness of this Sampling Search Procedure especially in areas where formal optimization cannot or should not be used.