| Article ID: | iaor19992089 |
| Country: | United Kingdom |
| Volume: | 47 |
| Issue: | 1 |
| Start Page Number: | 31 |
| End Page Number: | 48 |
| Publication Date: | Jan 1998 |
| Journal: | Applied Statistics |
| Authors: | Welch William J., Aslett Robert, Buck Robert J., Duvall Steven G., Sacks Jerome |
| Keywords: | optimization |
In electrical engineering, circuit designs are now often optimized via circuit simulation computer models. Typically, many response variables characterize the circuit's performance. Each response is a function of many input variables, including factors that can be set in the engineering design and noise factors representing manufacturing conditions. We describe a modelling approach which is appropriate for the simulator's deterministic input–output relationships. Non-linearities and interactions are identified without explicit assumptions about the functional form. These models lead to predictors to guide the reduction of the ranges of the designable factors in a sequence of experiments. Ultimately, the predictors are used to optimize the engineering design. We also show how a visualization of the fitted relationships facilitates an understanding of the engineering trade-offs between responses. The example used to demonstrate these methods, the design of a buffer circuit, has multiple targets for the responses, representing different trade-offs between the key performance measures.