Prediction of Print Geometry and Electrical Performance of InkJet Printed Electrical Components Using Statistical Models for Closed Loop Control

The demand for multifunctional, customizable, fine conductive traces for complex flexible circuits is increasing owing to the advancements in materials and process platforms. Printed electronics are rapidly increasing and replacing traditional manufacturing techniques, especially in consumer electronics. Current generation platforms do not have methods to monitor the print output and correct the input parameters to achieve the target value of design dimensions and electrical resistance, inductance, and capacitance. The use of new ink materials requires the extensive design of experiments for the identification of the print parameter values, which would yield the design output on the print platform. High yield of the manufacturing process requires methods for correcting the print parameters over long print runs to accommodate variations in the incoming materials and the print conditions. This paper discusses the development of closed-loop control based on statistical regression models for correcting deviations in the geometrical and electrical characteristics of electrical components printed using particle-free silver ink on the InkJet Platform. The statistical models have been developed using a design-of-experiments (DOE) matrix. The dependence of the print output, including the realized dimensions and electrical performance, has been correlated with the input parameters. The final aim of this paper is to have a statistical model to achieve desired print geometry and electrical performance.