This work reports on inkjet- and 3D-printed force/pressure sensing devices. The employed printing processes can enable cost- and resource-efficient, fast and flexible designs compared to solid-state technology which is used as a reference design. The pressure sensing devices are realized as either 3D-printed steel or 3D-printed ceramic diaphragms. Both designs thus withstand harsh environmental conditions and elevated temperatures. Additionally, the increased size guarantees less sensitivity to dirt or moisture due to the larger diameter of the diaphragms. The hardware used for the capacitive sensor read-out is based on a shunt measurement system and subsequent demodulation. This architecture enables long cabling, allowing for large parasitic capacitances, without significant loss of transferred signal power, due to the employed power matching to the transmission line. Physical analyses such as contact angle measurements, profilometer measurements, and focused ion beam analysis are done to characterize the resulting printed surfaces. Then, the response of both designs is evaluated by applying force on the diaphragms surface using a moveable load cell. The gathered results are also compared to finite element method simulations.

Purpose: This paper aims to investigate the optimal placement and/or orientation of individual sensor elements within integrated angular position sensors, in particular magnetic sensors based on the Hall effect or magnetoresistive effects under consideration of random deviations (variations in the production process, environmental influences, noise) and correlations of these influences. Design/methodology/approach: The authors utilize methods from optimal design of experiments to consider random deviations in a system-level model. In this sensor model, they include spatial dependencies of random deviations by means of a Gaussian random field. Based on this, an approach for fast determination of D-optimal designs is presented. Findings: The results show that the intuitive and commonly used distributions of magnetic field sensors are actually optimal for the determination of in-phase and quadrature signals in the presence of spatial correlations, provided that the number of field sensors is higher or equal to three. However, in the uncorrelated case, the intuitive solutions are not the only optimal solutions or even not optimal at all. It is found that a restriction to symmetric designs is not necessary; thus, the design space can be extended to allow for further improvements, e.g. miniaturization, of such angular position sensors. Originality/value: The proposed approach allows for the fast optimization based on a system model. Correlated random influences are considered by means of a Gaussian random field, which can be obtained either from measurements or from field simulations, e.g. using the finite element method. As this is done before the actual simulation, such evaluations are not needed during the optimization, which allows for very fast solution of the optimization problem. Therefore, the approach is well suited for application-dependent adjustment of sensor designs.