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Make or form wax or sand cores or molds used in the production of metal castings in foundries.
The occupation "Foundry Mold and Coremakers" has an automation risk of 45.8%, which closely aligns with its base risk estimate of 46.2%. This moderate percentage means that although almost half of the tasks could be replaced by automation, there remain significant barriers that prevent full mechanization. Many tasks within the occupation are repetitive and rule-based, making them prime candidates for automation technologies. However, the occupation also includes tasks that require nuanced human judgment or physical dexterity, holding back complete automation. Overall, the risk reflects a balance between highly automatable and more resistant task elements in this job. Among the most automatable tasks, cleaning and smoothing molds, cores, and core boxes, as well as repairing surface imperfections, rank first due to their repetitive and standardized nature. Similarly, sifting and packing sand into molds, often done with hand or pneumatic ramming tools, is a manual process that can easily be replicated by robots or automated machinery. Positioning patterns inside mold sections and clamping them together is another task that can be streamlined with automated production lines designed to handle uniform components at scale. These top three tasks highlight where automation has already made inroads, leveraging advancements in robotics and manufacturing automation. Conversely, some tasks remain resistant to automation, largely due to their complexity or the requirement for real-time problem-solving. Operating ovens or furnaces to bake cores or to melt, skim, and flux metal requires careful attention, safety awareness, and adaptive decision-making—factors that are difficult to fully automate. Pouring molten metal into molds, whether manually or with crane ladles, involves a combination of timing, precision, and safety handling that necessitates a human touch. Additionally, rotating sweep boards around spindles to make symmetrical molds demands spatial judgment and fine motor skills. The main bottleneck skills for automating these resistant tasks are low levels of originality (2.0% and 1.4%), indicating that while the work does not demand high creativity, it still requires problem-solving and adaptability that current automation technologies struggle to replicate.