Exploratory Perspectives on Artificial Intelligence Enabled Autonomous Manufacturing

Manufacturing spans complex materials properties and process variables. Currently, process development relies on empirical analysis, trial-and-error, and ex-situ characterization, limiting production efficiency and yield. Recently, artificial intelligence (AI) coupled with in-situ, in-line metrology has enabled autonomous characterization, data analysis, and rapid development of process-property correlations — necessary components in a future accelerated manufacturing paradigm. In this report, we share perspectives on applying AI and machine learning (ML) to roll-to-roll (R2R) coating of formulated inks — a scalable high-throughput manufacturing process used for many energy storage and conversion technologies including lithium-ion battery (LIB) electrodes and fuel cell and water electrolyzer membrane electrode assemblies (MEAs).