The arrays most commonly used in the design of experiments are the orthogonal arrays. These arrays are balanced: there are an equal number of levels for each factor in the experiments. The behavior of...

The objectives of DoE are to adjust the quality characteristics (or design or process output) to the optimum performance by properly choosing the best combination of factors and levels, as shown in Fi...

Design of experiments (DoE) is a systematic method for determining the effect of factors and their possible interactions in a design or a process toward achieving a particular output of the quality ch...

Accurate estimation of new product cost and quality is becoming very important for electronic enterprises. A good understanding of how cost and quality affect major decisions in material and process s...

The test and repair cost driver in Table 6.7 is a historical estimate in the technology-based cost model, and is based on previous or similar products FTY yields. In the quality-based cost model, test...

The quality of current products and manufacturing processes is dependent on their history and original design parameters....

For the hipot experiment, the initial ANOVA table is constructed in Table 7.15. An example is given at the top of how to calculate the sum of the squares for factor A....

Statistical analysis of DoEs is based on the analysis of variance (ANOVA), which is a method of determining the significance of each factor in terms of its effects on the output quality characteristic...