Statistical process control of commercial force-sensing resistors

Abstract

The manufacturing and characterization of polymer nanocomposites is an active research trend nowadays. Nonetheless, statistical studies of polymer nanocomposites are not an easy task since they require several factors to consider, such as: large amount of samples manufactured from a standardized procedure and specialized equipment to address characterization tests in a repeatable fashion. In this manuscript, the experimental characterization of sensitivity, hysteresis error and drift error was carried out at multiple input voltages (����) for the following commercial brands of FSRs ( force sensing resistors): Interlink FSR402 and Peratech SP200-10 sensors. The quotient between the mean and the standard deviation was used to determine dispersion in the aforementioned metrics. It was found that a low mean value in an error metric is typically accompanied by a comparatively larger dispersion, and similarly, a large mean value for a given metric resulted in lower dispersion; this observation was held for both sensor brands under the entire range of input voltages. In regard to sensitivity, both sensors showed similar dispersion in sensitivity for the whole range of input voltages. Sensors’ characterization was carried out in a tailored test bench capable of handling up to 16 sensors simultaneously; this let us speed up the characterization process.

Keywords

• sensing resistors (fsr)
• pressure sensor
• statistical process control
• hysteresis error
• drift error