Manufacturing Cycle-Time Optimization Using Gaussian Drying Model for Inkjet-Printed Electronics

Inkjet-printed electronics have attracted considerable attention for low-cost mass production. To avoid undesired device behavior due to accidental ink merging and redistribution, high-density designs can benefit from layering and drying in batches. The overall manufacturing cycle-time, however, now becomes dominated by the cumulative drying time of these individual layers. The state-of-the-art approach decomposes the whole design, arranges the modified objects in different layers, and minimizes the number of layers. Fewer layers imply a reduction in the number of printing iterations and thus a higher manufacturing efficiency. Nevertheless, printing objects with significantly different drying dynamics in the same layer leads to a reduction of manufacturing efficiency, since the longest drying object in a given layer dominates the time required for this layer to dry. Consequently, an accurate estimation of the individual layers’ drying time is indispensable to minimize the manufacturing cycle-time. To this end, we propose the first Gaussian drying model to evaluate the local evaporation rate in the drying process. Specifically, we estimate the drying time depending on the number, area, and distribution of the objects in a given layer. Finally, we minimize the total drying time by assigning to-be-printed objects to different layers with mixed-integer-linear programming (MILP) methods. Experimental results demonstrate that our Gaussian drying model closely approximates the actual drying process. In particular, comparing the non-optimized fabrication to the optimized results demonstrates that our method is able to reduce the drying time by 39%.