Study of the optimization of embroidery design parameters for the Technical Embroidery Machine: derivation of the correlation between thread consumption and electrical resistance

The smart textile industry has become increasingly interested in textile products with electronic functions. In these smart textile products, sensing and data communication are conducted through conductive circuits by conductive threads. In embroidery technology that uses conductive threads as the material for the conductive line as a circuit, their resistance is an important factor when designing a product. The main purpose of this study was to derive an equivalent circuit model and a calculation equation for the consumption of conductive threads according to the embroidery design parameters. The effects of the embroidery design parameters on the appearance and electrical characteristics of the conductive line were also analyzed. The appearance and electrical characteristics of the embroidered conductive line were different when the embroidery design parameters were not the same. The calculation equation for the consumption of conductive threads could establish a quantitative system that could indicate the line resistance of an embroidered conductive line using the embroidery design parameters and the given thread resistance.

Minimization of the Line Resistance Impact on Memdiode-Based Simulations of Multilayer Perceptron Arrays Applied to Pattern Recognition

In this paper, we extend the application of the Quasi-Static Memdiode model to the realistic SPICE simulation of memristor-based single (SLPs) and multilayer perceptrons (MLPs) intended for large dataset pattern recognition. By considering ex-situ training and the classification of the hand-written characters of the MNIST database, we evaluate the degradation of the inference accuracy due to the interconnection resistances for MLPs involving up to three hidden neural layers. Two approaches to reduce the impact of the line resistance are considered and implemented in our simulations, they are the inclusion of an iterative calibration algorithm and the partitioning of the synaptic layers into smaller blocks. The obtained results indicate that MLPs are more sensitive to the line resistance effect than SLPs and that partitioning is the most effective way to minimize the impact of high line resistance values.