Taguchi's product-array design consists of two portions: an inner array containing the design factors and an outer array containing noise factors. The function of the outer array is very different from that of the inner array, however. The outer array is most likely to sample or simulate the distribution of the noise factors, while the inner array is designated to facilitate the optimization. Since performance for each inner point is evaluated via its corresponding outer array points, the outer array plays an important role in robust design. We show here that the optimal representative point method via quantizer is superior to using other methods (including orthogonal array) to design outer array points. All optimal representative points are tabulated for practical use. The usage of these tables is demonstrated by examples.
All Science Journal Classification (ASJC) codes
- Safety, Risk, Reliability and Quality
- Strategy and Management
- Management Science and Operations Research
- Industrial and Manufacturing Engineering