Abstract

Among the many tasks designers must perform, evaluation of product options based on performance criteria is fundamental. Yet I have found that the methods commonly used remain controversial and uncertain among those who apply them. In this paper, I apply mathematical measurement theory to analyze and clarify common design methods. The methods can be analyzed to determine the level of information required and the quality of the answer provided. Most simple, a method using an ordinal scale only arranges options based on a performance objective. More complex, an interval scale also indicates the difference in performance provided. To construct an interval scale, the designer must provide two basic a priori items of information. First, a base-pointdesign is required from which the remaining designs are relatively measured. Second, the deviation of each remaining design is compared from the base point design using a metricdatum design. Given these two datums, any other design can be evaluated numerically. I show that concept selection charts operate with interval scales. After an interval scale, the next more complex scale is a ratio scale, where the objective has a well-defined zero value. I show that QFD methods operate with ratio scales. Of all measurement scales, the most complex are extensively measurable scales. Extensively measurable scales have a well defined base value, metric value and a concatenation operation for adding values. I show that standard optimization methods operate with extensively measurable scales. Finally, it is also possible to make evaluations with non-numeric scales. These may be more convenient, but are no more general.

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