**3. The Design Of Experiment methodology**

## **3.1. Introduction**

The Design Of Experiment methodology is based on statistical analysis and provides a semiempirical model in a similar way than limited development. Indeed, a response (laser hole drilling depth, for instance) can be described by a polynomial function of several parameters in a restricted domain through multilinear regression. Opposed to the Change One Separate factor at a Time (COST) method, DOE saves time and resources (human, machine, costs, sample, etc.) and is more relevant when parameters have a coupled effect on the response. It is a powerful tool to rule out noninfluent parameters (screening), describe, test the robustness or even optimize a process with a minimum of experimental trials. It is widely used in the industry to develop new products/process or improve existing ones, improve the quality, reduce the production costs, or the impact on the environment and even evaluate the influence of perturbations on a process (temperature, humidity, etc.) [28, 29].

The following sections propose to explore the use of this method in laser-based applications and to discuss the study of dicing silicon carbide substrates in the microelectronics industry.
