Drilling and Boring Machine Tool Setters, Operators, and Tenders, Metal and Plastic

Set up, operate, or tend drilling machines to drill, bore, ream, mill, or countersink metal or plastic work pieces.

The occupation "Drilling and Boring Machine Tool Setters, Operators, and Tenders, Metal and Plastic" has an automation risk rating of 34.9%, which is closely aligned with its base risk of 35.3%. This indicates that while automation is possible for a significant portion of the work, a considerable amount of the job still relies on human intervention. The occupation primarily involves the setup, operation, and tending of drilling and boring machines, making it susceptible to automation where repetitive, precise tasks can be executed by machinery. Modern advancements in CNC (computer numerical control) technology and robotics further amplify this risk by allowing machines to perform consistent and highly accurate tasks with minimal human oversight. Nonetheless, the relatively moderate risk score suggests there are core aspects of the job that remain difficult to automate. The most automatable tasks in this occupation include verifying the conformance of machined work to specifications using precision measuring instruments, studying machining instructions or blueprints, and moving machine controls to lower tools and engage automatic feeds. These activities are structured, rely heavily on consistent procedures, and can often be replicated using automation and sensor technologies. For instance, automated probing systems can measure workpieces, and advanced software can interpret blueprints and sequence operations with high accuracy. Additionally, the physical act of manipulating machine controls is well-suited for automation, as many modern systems can be programmed for repetitive tool movements and machine engagement. Conversely, several key tasks resist automation. Operating tracing attachments to duplicate physical contours, sharpening cutting tools with hand-operated grinders, and laying out reference lines with layout tools all require a degree of manual dexterity, adaptability, and shop math knowledge that current AI and robotics struggle to replicate. These tasks often call for nuanced judgment, physical sensitivity, and on-the-fly adjustments in response to material irregularities. The most significant bottleneck skill identified is originality, with a relative importance level of 2.1% and 2.0%. While this percentage may seem low, it highlights that the ability to devise novel solutions, adapt processes, and problem-solve in unpredictable scenarios presents a genuine hurdle for complete automation, helping to explain why the risk does not exceed one-third of total job functions.