Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing a process of manufacturing a product. In one aspect, the method comprises repeatedly performing the following: i) selecting a configuration of input settings for manufacturing a product, based on a causal model that measures causal relationships between input settings and a measure of a quality of the product; ii) determining the measure of the quality of the product manufactured using the configuration of input settings; and iii) adjusting, based on the measure of the quality of the product manufactured using the configuration of input settings, the causal model.

Abstract: A method and associated system provides automated abrasive paint repair using automated abrasive paint repair devices that selectively sand, buff, and polish a substrate in response to received instructions generated by a controller. The controller receives coordinates of each identified defect in the substrate along with parameters describing characteristics of each defect, selects a sanding process, a buffing process, and/or a polishing process based on empirically derived rules established by skilled/expert human operators and the received parameters. The controller outputs instructions to cause the automated abrasive paint repair devices to execute the selected sanding process, buffing process, and/or polishing process using the received parameters. The empirically derived rules and parameters may be stored in a lookup table and/or updated by a machine learning module.

Abstract: Methods of preparing metal oxide nanoparticles are described. The methods involve the thermal decomposition of a metal-carboxylate complex within a continuous, flow-through, tubular reactor. The resulting metal oxide nanoparticles contain iron and can be magnetic, non-agglomerated, crystalline or a combination thereof.