Factorial experimental design based on multiple factors for sensors and actuators development

This paper presents several use cases for a full factorial experimental design method used in the development of flexible sensors and actuators. The full factorial experimental designs consisted of 4 factors with discrete values (3–4 levels) based on known parameters of the experimental devices. In general, the selected factors can influence other dependent variables. This study aims to investigate the main effects and the interaction effects (antagonistic, synergistic, ceiling) among the different factors and to optimize an experimental design for reducing the consumption (raw materials, water, energy, chemicals) and obtaining the optimal values for surface electrical resistance using a reduced number of experiments. The use of the complete factorial experimental plan and optimization with a minimization function helps to select, from the set of possible experiments, the experiments including the optimal parameters for obtaining the desired result. Therefore, the number of experimental plans and the corresponding amount of resource consumption is reduced (e.g., from 81–256 experiments to 10–20 experiments) while obtaining electroconductive textile electrodes for sensors and actuators.