# Parametric Study of Geometry and Process Parameter Influences on Additively Manufactured Piezoresistive Sensors Under Cyclic Loading

## TL;DR

This study explores how material and printing parameters affect the performance of 3D-printed piezoresistive sensors under repeated stress.

## Contribution

The work provides a parametric analysis linking material, design, and printing parameters to sensor performance under cyclic loading.

## Key findings

- Nonlinearity and hysteresis errors in sensors are significantly influenced by material and printing parameters.
- Optimal parameter selection can reduce nonlinearity by up to 30.7% and hysteresis by up to 38.7%.
- Drift during repeated cycles is strongly material-dependent but also affected by process parameters like infill angle.

## Abstract

The additive manufacturing of piezoresistive sensors offers several advantages, such as the elimination of assembly or installation steps, enabling integration into complex parts precisely where desired, and compatibility with soft robotics applications. Previous studies have demonstrated that several characteristics of additively manufactured sensors, such as their resistance and sensitivity, are significantly affected by the selected printing parameters. This work seeks to further the understanding of the relationships between process parameters, material, sensor design, and the resulting sensor characteristics. To this end, sensors made from two materials, with differing printing layer heights, infill angles, and thicknesses, are characterized under cyclic tensile loading. For these sensors, the nonlinearity, hysteresis, and drift are analyzed. The findings indicate that both nonlinearity and hysteresis are significantly affected by the material choice, as well as the selected parameters. Notably, parameters that affect the sensitivity of the sensor, e.g., the infill angle, can have significant indirect effects on the nonlinearity and hysteresis errors. Through correct parameter selection, nonlinearity errors can be reduced by up to 30.7% or 25.3%, depending on the material used. The hysteresis error can be reduced by up to 38.7% or 23.8%, depending on the material. The drift over multiple cycles is found to be strongly material dependent, but can also be affected by the process parameters, e.g., the infill angle. Understanding the interactions between material, design, process, and the resulting sensor characteristics provides valuable insights for the successful design and additive manufacturing of piezoresistive sensors.